Data Scientist jobs at MissionBox

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what's next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. About the Role We're seeking a Staff Data Scientist to develop and deploy machine learning solutions for consumer growth, including fraud detection, pricing optimization, and user behavior modeling. You'll combine strong technical skills with a passion for learning to build scalable ML systems that drive business impact. This role requires a blend of strong research skills, mathematical rigor, and production-grade engineering practices. You will also act as a mentor to junior scientists, collaborate cross-functionally with product, engineering, and business stakeholders, and advance the company's research agenda through thought leadership and, when possible, publications in top-tier venues. Key Responsibilities End-to-End Delivery: Build complete ML pipelines from data processing to model deployment and monitoring in production environments ML Development: Design and implement machine learning models for growth applications, from classical algorithms to deep learning approaches Cross-Functional Collaboration: Work closely with product, engineering, and senior researchers to translate requirements into effective ML solutions Mentorship: Guide junior data scientists and contribute to team knowledge sharing Research & Innovation: Stay current with ML research and explore new methodologies relevant to consumer growth challenges Required Qualifications Education: PhD/MS in Machine Learning, Data Science, or closely related field Experience: 3+ years (PhD) or 5+ years (MS) of hands-on machine learning experience Technical Skills: Proficient in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost) Experience with SQL and large-scale data processing Proven track record deploying ML models to production Mindset: Strong desire to learn new techniques and adapt to evolving business needs Communication: Ability to clearly articulate ML concepts to diverse stakeholders Preferred Qualifications Experience in consumer-facing applications (growth, fraud, personalization) Familiarity with distributed computing systems (Spark, Ray) Publications in ML conferences or contributions to open-source projects How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at ******************************* along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery's total compensation package for employees. Pay Range: $145,600.00 - $270,400.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.If you're a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Current is a leading consumer fintech platform transforming financial access for everyday Americans with over five million members. We provide access to financial solutions that seamlessly work together to solve the needs of our members and enable all Americans to build better financial futures. Based in NYC, our results-driven environment drives us to build better products, grow faster and empower everyone on our team to have an impact on our business and mission to improve financial outcomes. We are in search of an experienced Data Scientist to lead our ML model development for our lending and liquidity products. In this role, you will leverage VertexAI to lead the design, development, deployment, and governance of machine learning models that power and optimize our risk underwriting to achieve business objectives. The ideal candidate will possess a strong background in statistical analysis, machine learning techniques, and programming, and preferably a solid understanding of the Credit Risk domain and VertexAI's capabilities, along with experience in deploying and scaling models using Scala and Google Dataflow. Responsibilities: Design, develop, and deploy models that are used for risk underwriting, risk management, limit setting, pricing, and customer acquisition and engagement optimization. Analyze diverse datasets, including but not limited to credit bureau, customer behavior, and alternative data, to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation. Lead and mentor a team of data scientists and analysts, providing guidance and support. Conduct exploratory data analysis, feature engineering, and model selection to optimize performance and enhance predictive accuracy. Implement and maintain scalable machine learning pipelines and workflows on Google Cloud Platform, ensuring reliability, scalability, and efficiency. Leverage Google Dataflow to process large-scale data and build scalable data processing pipelines. Evaluate model performance and govern deployed models using appropriate metrics, techniques, and scalable automated methods. Maintain model documentation and perform ongoing refits/retraining of existing models to ensure models are always at or near optimal performance and risks of degradation are avoided or managed. Design experiments, measure, test, and conduct readouts to optimize and test the underwriting process, offers, and customer engagement. Collaborate with engineering teams to integrate machine learning models into production systems, monitor performance, and troubleshoot issues. Contribute to developing best practices, standards, and documentation for machine learning processes and methodologies. Develop and implement data-driven strategies for credit risk management. Requirements: 7+ years of experience in data science or machine learning roles, with expertise in developing and deploying machine learning models, preferably with a background in consumer credit risk and the lending space. 2+ years of experience leading and managing data scientists and/or data analysts. Degree in Computer Science, Statistics, Mathematics, or a related field. Proficiency in Python programming and machine learning libraries (e.g., TensorFlow, scikit-learn) for model development and deployment. Proficiency in data preprocessing, feature engineering, and model selection techniques to optimize performance. Familiarity with Google Cloud Platform services, particularly VertexAI and Dataflow, for scalable data processing and model training. Proficiency in SQL and at least one programming language for developing scalable and efficient machine learning solutions. Understanding of credit risk models and methodologies. Strong leadership, communication, and collaboration skills. Ability to work effectively in a fast-paced, cross-functional environment. Strong understanding of statistical analysis, hypothesis testing, and experiment design. Excellent problem-solving skills with the ability to translate business requirements into technical solutions. Preferred: Experience using the Scala programming language for developing scalable and efficient machine learning solutions. 2+ years of experience building and deploying models using Vertex AI. Experience in B2C Fintech or Financial Services domain(s). This role has a base salary range of $215,000- $275,000. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits. Benefits: Competitive salary Meaningful equity in the form of stock options 401(k) plan Discretionary performance bonus program Biannual performance reviews Medical, Dental and Vision premiums covered at 100% for you and your dependents Flexible time off and paid holidays Generous parental leave policy Commuter benefits Fitness benefits Healthcare and Dependent care FSA benefit Employee Assistance Programs focused on mental health Healthcare advocacy program for all employees Access to mental health apps Team building activities Our modern Chelsea-based office with open floor plan, stocked kitchen, and catered lunches

Campus is on a mission to accelerate the talent of tomorrow and reimagine what college can (and should) be. The problem is clear: college costs have skyrocketed, but outcomes haven't. Traditional college hasn't kept up with the aspirations of today's students-and they can't afford to wait. At Campus, we've built a two-year, accredited college where students learn from top professors at universities like Princeton, Stanford, and Howard, in live, online classes. Our students graduate with in-demand business and AI skills-ready to launch their careers or transfer to top four-year universities. Our unique approach is grounded in a pioneering technology platform and a heavily-researched student success model that offers students dedicated advisors and on-demand tutoring and coaching. We were also named one of Fast Company's Most Innovative Companies of 2024. We're backed by an exceptional investor team that believes deeply in our vision for the future of education, including General Catalyst, Founders Fund, Bloomberg Beta, 8VC, Rethink Education, Sam Altman, Jason Citron, Shaquille O'Neal, and others. The world has changed. Higher ed needs to catch up, and we're leading the way - come join us! About the role We are seeking a Staff Data Scientist to help make Campus a world-class data-driven organization. This role requires deep analytical expertise, strong technical acumen, and a strategic mindset to turn data into actionable insights that directly improve student acquisition, engagement, and retention. You'll partner closely with teams across the company to design experiments, build predictive models, and deliver insights that influence key business outcomes. You're excited about this opportunity because you will… Develop a deep understanding of Campus students by creating predictive models for acquisition, admission, enrollment, and retention Build a unified student funnel dashboard integrating marketing, admissions, and retention metrics Identify and execute top opportunities to improve student retention using causal inference and experimentation Design and analyze A/B tests and causal inference frameworks to evaluate new product features and funnel improvements Partner cross-functionally with Marketing, Student Success, and Engineering teams to optimize acquisition and engagement experiments for measurable lift We're excited about you because… You are a strategic thinker who can connect data to key business objectives and communicate insights clearly You have an ownership mindset and thrive in environments where you define scope, drive projects, and deliver results independently You are a collaborative problem solver who enjoys working with both technical and non-technical partners You have a passion for education, experimentation, and growth analytics-and want to use your skills to make a meaningful impact You bring rigor, curiosity, and creativity to every analysis you conduct What you'll get: A compensation package that includes a base salary ($200K-$245K) + equity grant Actual compensation within the pay range will be decided based on factors including, but not limited to, skills, prior relevant experience, and specific work location. For roles that are available to be filled remotely, base salary will be localized. Medical, dental, and vision insurance 401(k) match Fertility benefits via Carrot Flexible Time Away + paid holidays In-office lunches for our NY Office (did we mention, we're dog friendly? 🐶) Hybrid work schedule (Mon & Fri remote; Tues-Thurs in-office) Social events - happy hours, birthday celebrations, holiday parties, & more! Opportunity to make an impact - you'll be an integral player in bringing our vision to life Where we're located: Tribeca, NY Unfortunately, we are unable to offer new H-1B visa sponsorship for this position. Candidates must already be authorized to work in the U.S. without requiring new H-1B sponsorship. However, we can support H-1B transfers and are able to sponsor TN visas for eligible Canadian and Mexican citizens.

Marketing science - a sub-team within marketing analytics at Disney's Direct to Consumer team (Hulu, Disney+, ESPN+ and Star) - is in search of an econometrician to run marketing mix models (MMM) and associated ancillary analysis. This position will work as part of a team focused primarily on econometric modeling, which also provides support for downstream practices used to inform marketing investment. The analyst plays a hands-on role in modeling efforts. The ideal candidate has a substantial quantitative skill set with direct experience in marketing science practices (MMM, attribution modeling, testing / experimentation, etc.), and should serve as a strong mentor to analysts, helping to onboard new talent in support of wider company goals. Technical acumen as well as narrative-building are integral to the success of this role. Responsibilities Build, sustain and scale econometric models (MMM) for Disney Streaming Services with support from data engineering and data product teams Quantify ROI on marketing investment, determine optimal spend range across the portfolio, identify proposed efficiency caps by channel, set budget amounts and inform subscriber acquisition forecasts Support ad hoc strategic analysis to provide recommendations that drive increased return on spend through shifts in mix, flighting, messaging and tactics, and that help cross-validate model results Provide insights to marketing and finance teams, helping to design and execute experiments to move recommendations forward based on company goals (e.g., subscriber growth, LTV, etc) Support long-term MMM (et.al.) automation, productionalization and scale with support from data engineering and product Build out front-end reporting and dashboarding in partnership with data product analysts and data engineers to communicate performance metrics across services, markets, channels and subscriber types Basic Qualifications Bachelor's degree in advanced Mathematics, Statistics, Data Science or comparable field of study 3+ years of experience in a marketing data science / analytics role with understanding of measurement and optimization best practices Coursework or direct experience in applied econometric modeling, ideally in support of measure marketing efficiency and optimize spend, flighting and mix to maximize return on ad spend (i.e., MMM) Exposure / understanding of media attribution practices for digital and linear media, the data to power them and methodologies for measurement Understanding of incrementality experiments to validate model recommendations and gain learnings on channel/publisher efficacy Exposure to / familiarity with with BI/data concepts and experience building out self-service marketing data solutions Strong coding experience in one (or more) data programming languages like Python/R Ability to draw insights and conclusions from data to inform model development and business decisions Experience in SQL Preferred Qualifications Masters degree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics The hiring range for this position in Santa Monica, CA is $117,500 to $157,500 per year and in New York City, NY & Seattle, WA is $123,000 to $165,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. Job Posting Segment: Direct to Consumer Job Posting Primary Business: DTC Analytics and Data Science Primary Job Posting Category: Data Science Employment Type: Full time Primary City, State, Region, Postal Code: New York, NY, USA Alternate City, State, Region, Postal Code: USA - CA - 1200 Grand Central Ave, USA - CA - 2500 Broadway Street, USA - WA - 925 4th Ave Date Posted: 2025-12-01

Marketing science - a sub-team within marketing analytics at Disney's Direct to Consumer team (Hulu, Disney+, ESPN+ and Star) - is in search of an econometrician to run marketing mix models (MMM) and associated ancillary analysis. This position will work as part of a team focused primarily on econometric modeling, which also provides support for downstream practices used to inform marketing investment. The analyst plays a hands-on role in modeling efforts. The ideal candidate has a substantial quantitative skill set with direct experience in marketing science practices (MMM, attribution modeling, testing / experimentation, etc.), and should serve as a strong mentor to analysts, helping to onboard new talent in support of wider company goals. Technical acumen as well as narrative-building are integral to the success of this role. **Responsibilities** + Build, sustain and scale econometric models (MMM) for Disney Streaming Services with support from data engineering and data product teams + Quantify ROI on marketing investment,determineoptimalspend range across the portfolio,identifyproposed efficiency caps by channel, set budgetamountsand inform subscriber acquisition forecasts + Support ad hoc strategic analysis to provide recommendations that drive increased return on spend through shifts in mix, flighting,messagingand tactics, and that help cross-validate model results + Provide insights to marketing and finance teams, helping to design and execute experiments to move recommendations forward based on company goals (e.g., subscriber growth, LTV,etc) + Support long-term MMM (et.al.) automation,productionalizationand scale with support from data engineering and product + Build out front-end reporting and dashboarding in partnership with data product analysts and data engineers to communicate performance metrics across services, markets,channelsand subscriber types **Basic Qualifications** + Bachelor's degree in advanced Mathematics, Statistics, DataScienceor comparable field of study + 3+ years of experience in a marketing data science / analytics role with understanding of measurement and optimization best practices + Coursework or direct experience in applied econometric modeling, ideally in support of measure marketing efficiency andoptimizespend, flighting and mix to maximize return on ad spend (i.e., MMM) + Exposure / understanding of media attribution practices for digital and linear media, the datarequiredto power them and methodologies for measurement + Understanding of incrementality experiments tovalidatemodel recommendations and gain learnings on channel/publisher efficacy + Exposure to / familiarity withwith BI/data concepts and experience building out self-service marketing data solutions + Strong coding experience in one (or more) data programming languages like Python/R + Ability to draw insights and conclusions from data to inform model development and business decisions + Experience in SQL **Preferred Qualifications** + Mastersdegree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics The hiring range for this position in Santa Monica, CA is $117,500 to $157,500 per year and in New York City, NY & Seattle, WA is $123,000 to $165,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. **Job ID:** 10137431 **Location:** New York,New York **Job Posting Company:** Disney Direct to Consumer The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, email Candidate.Accommodations@Disney.com with your request. This email address is not for general employment inquiries or correspondence. We will only respond to those requests that are related to the accessibility of the online application system due to a disability.

Marketing science - a sub-team within marketing analytics at Disney's Direct to Consumer team (Hulu, Disney+, ESPN+ and Star) - is in search of an econometrician to run marketing mix models (MMM) and associated ancillary analysis. This position will work as part of a team focused primarily on econometric modeling, which also provides support for downstream practices used to inform marketing investment. The analyst plays a hands-on role in modeling efforts. The ideal candidate has a substantial quantitative skill set with direct experience in marketing science practices (MMM, attribution modeling, testing / experimentation, etc.), and should serve as a strong mentor to analysts, helping to onboard new talent in support of wider company goals. Technical acumen as well as narrative-building are integral to the success of this role. Responsibilities * Build, sustain and scale econometric models (MMM) for Disney Streaming Services with support from data engineering and data product teams * Quantify ROI on marketing investment, determine optimal spend range across the portfolio, identify proposed efficiency caps by channel, set budget amounts and inform subscriber acquisition forecasts * Support ad hoc strategic analysis to provide recommendations that drive increased return on spend through shifts in mix, flighting, messaging and tactics, and that help cross-validate model results * Provide insights to marketing and finance teams, helping to design and execute experiments to move recommendations forward based on company goals (e.g., subscriber growth, LTV, etc) * Support long-term MMM (et.al.) automation, productionalization and scale with support from data engineering and product * Build out front-end reporting and dashboarding in partnership with data product analysts and data engineers to communicate performance metrics across services, markets, channels and subscriber types Basic Qualifications * Bachelor's degree in advanced Mathematics, Statistics, Data Science or comparable field of study * 3+ years of experience in a marketing data science / analytics role with understanding of measurement and optimization best practices * Coursework or direct experience in applied econometric modeling, ideally in support of measure marketing efficiency and optimize spend, flighting and mix to maximize return on ad spend (i.e., MMM) * Exposure / understanding of media attribution practices for digital and linear media, the data required to power them and methodologies for measurement * Understanding of incrementality experiments to validate model recommendations and gain learnings on channel/publisher efficacy * Exposure to / familiarity with with BI/data concepts and experience building out self-service marketing data solutions * Strong coding experience in one (or more) data programming languages like Python/R * Ability to draw insights and conclusions from data to inform model development and business decisions * Experience in SQL Preferred Qualifications * Masters degree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics The hiring range for this position in Santa Monica, CA is $117,500 to $157,500 per year and in New York City, NY & Seattle, WA is $123,000 to $165,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. About Disney Direct to Consumer: Disney's Direct to Consumer team oversees the Hulu and Disney+ streaming businesses within Disney Entertainment helping to bring The Walt Disney Company's best-in-class storytelling to fans and families everywhere. About The Walt Disney Company: The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise that includes three core business segments: Disney Entertainment, ESPN, and Disney Experiences. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney's stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished. This position is with Disney Streaming Services LLC, which is part of a business we call Disney Direct to Consumer. Disney Streaming Services LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, religion, color, sex, sexual orientation, gender, gender identity, gender expression, national origin, ancestry, age, marital status, military or veteran status, medical condition, genetic information or disability, or any other basis prohibited by federal, state or local law. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world. Apply Now Apply Later Current Employees Apply via My Disney Career Explore Location

Marketing science - a sub-team within marketing analytics at Disney's Direct to Consumer team (Hulu, Disney+, ESPN+ and Star) - is in search of an econometrician to run marketing mix models (MMM) and associated ancillary analysis. This position will work as part of a team focused primarily on econometric modeling, which also provides support for downstream practices used to inform marketing investment. The analyst plays a hands-on role in modeling efforts. The ideal candidate has a substantial quantitative skill set with direct experience in marketing science practices (MMM, attribution modeling, testing / experimentation, etc.), and should serve as a strong mentor to analysts, helping to onboard new talent in support of wider company goals. Technical acumen as well as narrative-building are integral to the success of this role. Responsibilities Build, sustain and scale econometric models (MMM) for Disney Streaming Services with support from data engineering and data product teams Quantify ROI on marketing investment, determine optimal spend range across the portfolio, identify proposed efficiency caps by channel, set budget amounts and inform subscriber acquisition forecasts Support ad hoc strategic analysis to provide recommendations that drive increased return on spend through shifts in mix, flighting, messaging and tactics, and that help cross-validate model results Provide insights to marketing and finance teams, helping to design and execute experiments to move recommendations forward based on company goals (e.g., subscriber growth, LTV, etc) Support long-term MMM (et.al.) automation, productionalization and scale with support from data engineering and product Build out front-end reporting and dashboarding in partnership with data product analysts and data engineers to communicate performance metrics across services, markets, channels and subscriber types Basic Qualifications Bachelor's degree in advanced Mathematics, Statistics, Data Science or comparable field of study 3+ years of experience in a marketing data science / analytics role with understanding of measurement and optimization best practices Coursework or direct experience in applied econometric modeling, ideally in support of measure marketing efficiency and optimize spend, flighting and mix to maximize return on ad spend (i.e., MMM) Exposure / understanding of media attribution practices for digital and linear media, the data required to power them and methodologies for measurement Understanding of incrementality experiments to validate model recommendations and gain learnings on channel/publisher efficacy Exposure to / familiarity with with BI/data concepts and experience building out self-service marketing data solutions Strong coding experience in one (or more) data programming languages like Python/R Ability to draw insights and conclusions from data to inform model development and business decisions Experience in SQL Preferred Qualifications Masters degree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics The hiring range for this position in Santa Monica, CA is $117,500 to $157,500 per year and in New York City, NY & Seattle, WA is $123,000 to $165,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. Job Posting Segment: Direct to Consumer Job Posting Primary Business: DTC Analytics and Data Science Primary Job Posting Category: Data Science Employment Type: Full time Primary City, State, Region, Postal Code: New York, NY, USA Alternate City, State, Region, Postal Code: USA - CA - 1200 Grand Central Ave, USA - CA - 2500 Broadway Street, USA - WA - 925 4th Ave Date Posted: 2025-12-01

Current is a leading U.S. fintech serving people who have been overlooked by traditional banks. We are one of the fastest-growing companies with nearly 4 million members. Headquartered in NYC, our results-driven environment empowers our team to build better products, grow faster, and have a direct impact on our mission to improve financial outcomes for our members. About the Role At Current, data is at the core of everything we do. As a Senior Data Scientist on the Data and Growth teams, you will focus on machine learning modeling to build predictive models that help us understand our customers better, improve user experience, and efficiently acquire and retain members. This is a hands-on role focused on solving complex problems, developing and deploying ML models, and driving data-driven decision-making. Your day-to-day will involve analyzing, preparing, and structuring data; building and optimizing predictive models; leveraging clustering algorithms; and collaborating with cross-functional teams (Product, Engineering, Marketing) to integrate ML solutions into customer-focused strategies and processes. Responsibilities Design, develop, and deploy predictive classification and regression models, along with anomaly detection models and algorithms. Conduct extensive EDA, feature engineering, and data preprocessing to ensure high-quality input for ML models. Evaluate and optimize model performance using statistical and ML techniques. Design and execute A/B tests to measure and validate model impact. Perform customer segmentation using various clustering techniques. Develop and implement model monitoring dashboards and establish model governance techniques. Collaborate with Analytics, Product, Engineering, and Marketing teams to seamlessly integrate predictive models into workflows. Work with the ML Engineering team to ensure efficient data pipelines and scalable model deployment. Analyze diverse datasets to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation. Qualifications About You 5+ years of experience in data science with a strong emphasis on machine learning modeling. Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch. Expertise in SQL and working with large, complex structured and semi-structured datasets. Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods. Experience in feature engineering, model selection, and performance optimization. Experienced in designing, executing, analyzing, and reporting on experiments. Strong communication skills and ability to present findings to technical and non-technical stakeholders. Master's or higher degree in Data Science, Computer Science, Statistics, or a related field is preferred. Preferred Skills & Qualifications Experience working in fintech, e-commerce, or other data-rich consumer-facing industries. Familiarity with Google Cloud Platform (GCP) services, particularly Vertex AI and Dataflow, for scalable data processing and model training. Experience with dbt for data modeling. Familiarity with BigQuery or other MPP (Massively Parallel Processing) databases. Experience using the Scala programming language for developing scalable and efficient data pipelines. Benefits Competitive salary Stock options 401(k) savings plan Discretionary performance bonus program Biannual performance reviews Medical, Dental and Vision premiums covered at 100% for you and your dependents Unlimited time off and paid holidays Generous parental leave policy Commuter benefits Healthcare and Dependent care FSA benefit Employee Assistance Programs focused on mental health Healthcare advocacy program for all employees Access to mental health apps Team building activities Our modern Chelsea-based office with open floor plan, stocked kitchen, and catered lunches This role has a base salary range of $170,000.00 - $220,000.00. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits.

Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation. About the Role: Tubi is transforming the future of television with a vast library of free, premium content supported by advertising. We're seeking a curious, strategic, and technically strong Senior Data Scientist to join our growing Data Science team-specifically supporting our Content function. In this high-impact role, you'll help drive smarter content decisions, power personalization strategies, and unlock viewer engagement through data. As a Senior Data Scientist at Tubi, you'll lead end-to-end analytical projects that shape what our viewers see and how they experience our platform. You'll work at the intersection of content strategy, product, marketing, and monetization, bringing a rigorous experimentation mindset and technical expertise to our most critical initiatives. Your work will be crucial in expanding our audience, optimizing our content library, and developing data-driven frameworks that scale with the business. You'll collaborate cross-functionally with content strategy, data engineering, product managers, and executives-ensuring that data and experimentation are deeply embedded in how we choose, evaluate, and present content. This is an exciting opportunity for someone passionate about streaming, thrives in ambiguity, and wants to influence the future of TV through data. What You'll Do: Design, execute, and analyze A/B tests and quasi-experiments that inform content acquisition, placement, and personalization strategies. Apply statistical rigor and causal inference methods to evaluate content performance and viewer engagement at scale. Work with large, complex datasets using SQL, Python, and Spark to uncover actionable insights that drive strategic content decisions. Develop and maintain dashboards, data products, and visualizations that translate data into clear business recommendations. Partner closely with cross-functional stakeholders to influence decisions with thoughtful, transparent, and evidence-based insights. Collaborate with Data Engineering and ML Ops to improve data pipelines, feature engineering, and automation across experimentation workflows. Serve as a thought partner across teams, advocating for best practices in experimentation, measurement, and data strategy. Your Background: 8+ years of experience in a data science, analytics, or quantitative research role, ideally in a consumer technology or media company. Advanced proficiency in SQL, Python, and Spark, with hands-on experience managing and analyzing large-scale, event-level data. Deep understanding of A/B testing, experimental design, and causal inference methodologies. Proven ability to translate data into compelling stories and recommendations for non-technical audiences. Experience with product analytics, content performance measurement, or personalization systems is a plus. Bachelor's degree in Statistics, Computer Science, Mathematics, Economics, or a related field. Experience in video streaming, entertainment, or ad-supported media is highly preferred. #LI-SL4 #LI-Hybrid Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is is listed annually below. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, a 401(k) plan, paid time off and other benefits in accordance with applicable plan documents. High cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco$151,800-$216,800 USDToronto, Ontario, Canada$110,800-$158,300 CAD Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of all US employee benefits. The following distinctions below outline the differences between the Tubi and FOX benefits: For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time. For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters. For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX's short-term disability policy. This time is 100% paid through a combination of any applicable state, city, and federal leaves and wage-replacement programs in addition to contributions made by Tubi. For all full-time, regular employees, Tubi offers a monthly wellness reimbursement. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.

About The Role & Team Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a Sr Data Scientist, where you'll transform complex data into strategic business decisions that shape the future of streaming entertainment. Collaborating closely with cross-functional partners across the Business, you'll architect and execute sophisticated experiments that optimize every aspect of the subscriber journey-from initial acquisition through long-term retention and revenue growth. As part of Disney's rapidly evolving streaming ecosystem, you'll tackle complex business challenges that directly impact millions of subscribers across Disney+, Hulu, and ESPN. Your insights will shape Product roadmaps, pricing strategies, and user experience optimizations that drive measurable business growth. What You'll Do Design and Execute Experiments: Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations Apply Causal Inference Methods: Leverage advanced techniques including difference-in-differences, instrumental variables, propensity score analysis, and other quasi-experimental designs to extract actionable insights from observational data Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders Qualifications Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field. 5+ years of experience conducting strategic analyses and communicating insights to drive decision-making. Expertise in Python, R, or similar languages, including experience building software packages for statistical analysis. Expertise in SQL. Proficient in analyzing data and developing ML models using Python (with ML frameworks like LGBM, scikit-learn, etc.). Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques. Demonstrated ability to translate complex data into clear and actionable narratives, and the ability to communicate opportunities and challenges to multiple stakeholders. Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling. Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches. Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes. Desired Qualifications Masters or PhD in quantitative field with an emphasis on experimentation or causal inference. Experience applying strategic thinking to analyze market trends and consumer insights, with preference for candidates who have worked with subscription-based business models. Ability to adapt quickly in a fast-moving environment with shifting priorities. Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github. The hiring range for this position in Santa Monica, CA is $141,900 to $190,300 per year, in San Francisco, CA is $155,400 to $208,400 and in New York City, NY is $148,700 to $199,400. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. Job Posting Segment: Direct to Consumer Job Posting Primary Business: DTC Analytics and Data Science Primary Job Posting Category: Data Science Employment Type: Full time Primary City, State, Region, Postal Code: New York, NY, USA Alternate City, State, Region, Postal Code: USA - CA - 2500 Broadway Street, USA - CA - Market St Date Posted: 2025-12-03

Cadent ignites seamless connections between brands, publishers & consumers. Our predictive AI orchestrates outcomes on any platform customers are on, across any media they consume & at any stage of the journey. To learn more, please visit thenewcadent.com. Right now, we are looking for a highly motivated Associate Data Scientist who will be responsible for applying scientific methods to identify business optimization strategies and develop, evaluate and demonstrate prototypes of empirical software including but not limited to machine learning, signal processing and optimization based numerical methods. Data Scientists collaborate directly with the Business, Product, Data Engineering, and QA team members to productize AI/ML research to drive business growth. This is a critical role that needs knowledge of mathematics and engineering, output from this role will be leveraged by business, engineers and by senior executives to define the future of Cadent. Responsibilities Design, train and apply statistics, mathematical models, and machine learning techniques to create scalable solutions to business problems Work with machine learning engineers and software developers to deploy models and modeling pipelines to be leveraged inside of business software products Contribute iterative improvements to predictive models Leverage model governance techniques and frameworks to ensure performance and stability of data science products Work with product team to align on product roadmap and goals with business vertical KPIs Participate in the Agile / scrum process Follow the CRISP-DM process to generate robust documentation associated with iterative work Present results and findings to technical audience, product and business stakeholders Collaborate effectively with other members of the data science team, engineering research team and broader data services group including but not limited to Machine Learning Engineers, Data Engineers, Analytics Engineers, Software Engineers, Quality Assurance Engineers, and Business Intelligence analysts Participate in researching new data, tools, algorithms and tech stack to align with evolving AI & ML industry Qualifications M.S. in Computer Science, Mathematics, Statistics, a related quantitative field, or equivalent practical experience with a focus on machine learning; or the equivalent of B.S with 2-3 years of experience in a similar role 0-1 years professional experience in a similar role. Proven background answering open ended research questions using data, tools and technology Ability to write clean, expressive code in Python and/or other tools including PySpark, Scala etc. Practical experience building and evaluating machine learning models, preferably with the scikit- learn ecosystem. Experience with SQL and reading from relational databases Experience using cloud computing ecosystems (e.g., AWS, GCP) is a plus Experience with the practical application of computational statistics Fundamental understanding of the mathematical workings of standard feature engineering, dimension reduction, machine learning algorithms and model validation & measurement Experience with the practical application of computational statistics and complex ML algos including deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models Demonstrated communication skills including the ability to switch between technical and business contexts Familiarity with best practices for software engineering and the use of the scientific Python ecosystem Knowledge of LLM technologies, including generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), and evaluation benchmarks Media or ad-tech experience a plus So, if the leading edge of media technology is the place you want to be, please contact us today and let's start the conversation! Cadent is an Equal Opportunity Employer and is committed to supporting all it's employees when it comes to Inclusion & Diversity. Cadent's policy is to provide equal opportunity for applicants & employees without regard to race, color, religion, creed, gender, gender identity or expression, sexual identity or orientation, age, national origin or ancestry, citizenship, disability or medical condition (including pregnancy, childbirth, or related medical condition), sexual and reproductive health decisions, genetic information, marital status (including domestic partnerships and civil unions), pregnancy, culture ancestry, familial or caregiver status, military status, veteran status, socioeconomic status, unemployment status, status as a victim of domestic violence or any other basis prohibited by law. and will not discriminate against the basis of disability. This commitment is honored when it comes to decisions on hiring, recruiting, training, promotions, compensations, benefits, transfers and terminations. Cadent is seeking to actively engage with our employees from a wide variety of cultures and to connect with our clients differently. Our workforce has generational diversity that supports greater innovation when we maximize representation of all diversity. Our active employee resource groups promote engagement across all groups of individuals that are represented within the company and externally. Pay Range USD $90,000.00 - USD $110,000.00 /Yr.

Cadent ignites seamless connections between brands, publishers & consumers. Our predictive AI orchestrates outcomes on any platform customers are on, across any media they consume & at any stage of the journey. To learn more, please visit thenewcadent.com. Right now, we are looking for a highly motivated Associate Data Scientist who will be responsible for applying scientific methods to identify business optimization strategies and develop, evaluate and demonstrate prototypes of empirical software including but not limited to machine learning, signal processing and optimization based numerical methods. Data Scientists collaborate directly with the Business, Product, Data Engineering, and QA team members to productize AI/ML research to drive business growth. This is a critical role that needs knowledge of mathematics and engineering, output from this role will be leveraged by business, engineers and by senior executives to define the future of Cadent. Responsibilities Design, train and apply statistics, mathematical models, and machine learning techniques to create scalable solutions to business problems Work with machine learning engineers and software developers to deploy models and modeling pipelines to be leveraged inside of business software products Contribute iterative improvements to predictive models Leverage model governance techniques and frameworks to ensure performance and stability of data science products Work with product team to align on product roadmap and goals with business vertical KPIs Participate in the Agile / scrum process Follow the CRISP-DM process to generate robust documentation associated with iterative work Present results and findings to technical audience, product and business stakeholders Collaborate effectively with other members of the data science team, engineering research team and broader data services group including but not limited to Machine Learning Engineers, Data Engineers, Analytics Engineers, Software Engineers, Quality Assurance Engineers, and Business Intelligence analysts Participate in researching new data, tools, algorithms and tech stack to align with evolving AI & ML industry Qualifications M.S. in Computer Science, Mathematics, Statistics, a related quantitative field, or equivalent practical experience with a focus on machine learning; or the equivalent of B.S with 2-3 years of experience in a similar role 0-1 years professional experience in a similar role. Proven background answering open ended research questions using data, tools and technology Ability to write clean, expressive code in Python and/or other tools including PySpark, Scala etc. Practical experience building and evaluating machine learning models, preferably with the scikit- learn ecosystem. Experience with SQL and reading from relational databases Experience using cloud computing ecosystems (e.g., AWS, GCP) is a plus Experience with the practical application of computational statistics Fundamental understanding of the mathematical workings of standard feature engineering, dimension reduction, machine learning algorithms and model validation & measurement Experience with the practical application of computational statistics and complex ML algos including deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models Demonstrated communication skills including the ability to switch between technical and business contexts Familiarity with best practices for software engineering and the use of the scientific Python ecosystem Knowledge of LLM technologies, including generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), and evaluation benchmarks Media or ad-tech experience a plus So, if the leading edge of media technology is the place you want to be, please contact us today and let's start the conversation! Cadent is an Equal Opportunity Employer and is committed to supporting all it's employees when it comes to Inclusion & Diversity. Cadent's policy is to provide equal opportunity for applicants & employees without regard to race, color, religion, creed, gender, gender identity or expression, sexual identity or orientation, age, national origin or ancestry, citizenship, disability or medical condition (including pregnancy, childbirth, or related medical condition), sexual and reproductive health decisions, genetic information, marital status (including domestic partnerships and civil unions), pregnancy, culture ancestry, familial or caregiver status, military status, veteran status, socioeconomic status, unemployment status, status as a victim of domestic violence or any other basis prohibited by law. and will not discriminate against the basis of disability. This commitment is honored when it comes to decisions on hiring, recruiting, training, promotions, compensations, benefits, transfers and terminations. Cadent is seeking to actively engage with our employees from a wide variety of cultures and to connect with our clients differently. Our workforce has generational diversity that supports greater innovation when we maximize representation of all diversity. Our active employee resource groups promote engagement across all groups of individuals that are represented within the company and externally. Pay Range USD $90,000.00 - USD $110,000.00 /Yr.

About The Role & Team Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a Sr Data Scientist, where you'll transform complex data into strategic business decisions that shape the future of streaming entertainment. Collaborating closely with cross-functional partners across the Business, you'll architect and execute sophisticated experiments that optimize every aspect of the subscriber journey-from initial acquisition through long-term retention and revenue growth. As part of Disney's rapidly evolving streaming ecosystem, you'll tackle complex business challenges that directly impact millions of subscribers across Disney+, Hulu, and ESPN. Your insights will shape Product roadmaps, pricing strategies, and user experience optimizations that drive measurable business growth. What You'll Do + **Design and Execute Experiments** : Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations + **Apply Causal Inference Methods** : Leverage advanced techniques including difference-in-differences, instrumental variables, propensity score analysis, and other quasi-experimental designs to extract actionable insights from observational data + **Build Scalable Solutions** : Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses + **Deliver Strategic Insights** : Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations + **Influence Executive Decisions** : Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders Qualifications + Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field. + 5+ years of experience conducting strategic analyses and communicating insights to drive decision-making. + Expertise in Python, R, or similar languages, including experience building software packages for statistical analysis. + Expertise in SQL. + Proficient in analyzing data and developing ML models using Python (with ML frameworks like LGBM, scikit-learn, etc.). + Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques. + Demonstrated ability to translate complex data into clear and actionable narratives, and the ability to communicate opportunities and challenges to multiple stakeholders. + Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling. + Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches. + Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes. Desired Qualifications + Masters or PhD in quantitative field with an emphasis on experimentation or causal inference. + Experience applying strategic thinking to analyze market trends and consumer insights, with preference for candidates who have worked with subscription-based business models. + Ability to adapt quickly in a fast-moving environment with shifting priorities. + Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github. The hiring range for this position in Santa Monica, CA is $141,900 to $190,300 per year, in San Francisco, CA is $155,400 to $208,400 and in New York City, NY is $148,700 to $199,400. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. **Job ID:** 10136962 **Location:** New York,New York **Job Posting Company:** Disney Direct to Consumer The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, email Candidate.Accommodations@Disney.com with your request. This email address is not for general employment inquiries or correspondence. We will only respond to those requests that are related to the accessibility of the online application system due to a disability.

About The Role & Team Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a Sr Data Scientist, where you'll transform complex data into strategic business decisions that shape the future of streaming entertainment. Collaborating closely with cross-functional partners across the Business, you'll architect and execute sophisticated experiments that optimize every aspect of the subscriber journey-from initial acquisition through long-term retention and revenue growth. As part of Disney's rapidly evolving streaming ecosystem, you'll tackle complex business challenges that directly impact millions of subscribers across Disney+, Hulu, and ESPN. Your insights will shape Product roadmaps, pricing strategies, and user experience optimizations that drive measurable business growth. What You'll Do * Design and Execute Experiments: Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations * Apply Causal Inference Methods: Leverage advanced techniques including difference-in-differences, instrumental variables, propensity score analysis, and other quasi-experimental designs to extract actionable insights from observational data * Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses * Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations * Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders Qualifications * Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field. * 5+ years of experience conducting strategic analyses and communicating insights to drive decision-making. * Expertise in Python, R, or similar languages, including experience building software packages for statistical analysis. * Expertise in SQL. * Proficient in analyzing data and developing ML models using Python (with ML frameworks like LGBM, scikit-learn, etc.). * Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques. * Demonstrated ability to translate complex data into clear and actionable narratives, and the ability to communicate opportunities and challenges to multiple stakeholders. * Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling. * Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches. * Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes. Desired Qualifications * Masters or PhD in quantitative field with an emphasis on experimentation or causal inference. * Experience applying strategic thinking to analyze market trends and consumer insights, with preference for candidates who have worked with subscription-based business models. * Ability to adapt quickly in a fast-moving environment with shifting priorities. * Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github. The hiring range for this position in Santa Monica, CA is $141,900 to $190,300 per year, in San Francisco, CA is $155,400 to $208,400 and in New York City, NY is $148,700 to $199,400. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered. About Disney Direct to Consumer: Disney's Direct to Consumer team oversees the Hulu and Disney+ streaming businesses within Disney Entertainment helping to bring The Walt Disney Company's best-in-class storytelling to fans and families everywhere. About The Walt Disney Company: The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise that includes three core business segments: Disney Entertainment, ESPN, and Disney Experiences. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney's stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished. This position is with Disney Streaming Services LLC, which is part of a business we call Disney Direct to Consumer. Disney Streaming Services LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, religion, color, sex, sexual orientation, gender, gender identity, gender expression, national origin, ancestry, age, marital status, military or veteran status, medical condition, genetic information or disability, or any other basis prohibited by federal, state or local law. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world. Apply Now Apply Later Current Employees Apply via My Disney Career Explore Location

Overview (Why This Role?) Hearst Magazines is seeking a visionary and hands-on Senior Data Scientist to join our dynamic Data & AI team. In this pivotal role, you will be a key player in architecting and implementing the advanced data models that power personalized user experiences, drive our next-generation advertising products, and provide deep, actionable insights to our world-class editorial and commercial teams. You will tackle complex challenges at the intersection of machine learning, user behavior, and content strategy, with a direct impact on the trajectory of our iconic brands. About Hearst Magazines ( Why Us?) Hearst Magazines' portfolio of more than 30 iconic brands in the U.S.-including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper's BAZAAR, and Popular Mechanics - inspires, entertains, and builds new and bold experiences for an engaged and growing audience across digital, video, social and print, reaching nearly 130 million readers and site visitors each month. With sophisticated content creation, cutting-edge technology, and industry-leading data capabilities, we make media and products that move people across all platforms. We are a global media company that publishes nearly 200 magazine editions and 175 websites around the world-and together, we are shaping what's next. Key Responsibilities(What are you doing) Lead and Innovate: Design, develop, and deploy sophisticated machine learning models to address core business challenges, including user segmentation, content recommendation, churn prediction, and lifetime value modeling. Strategic Impact: Partner with product, engineering, editorial, and revenue teams to identify and execute on data science initiatives that drive measurable business outcomes. Full-Cycle Development: Own the end-to-end data science workflow, from hypothesis generation and data exploration to model building, validation, and deployment into production environments. Advanced Analytics: Conduct in-depth exploratory analysis of large, complex datasets to uncover hidden patterns, trends, and opportunities for innovation. Mentorship: Provide guidance and mentorship to junior data scientists and analysts, fostering a culture of technical excellence and collaborative problem-solving. Thought Leadership: Stay at the forefront of advancements in data science and machine learning, and champion the adoption of new technologies and methodologies within the organization. Qualifications (What We're Looking For) Experience: 7+ years of experience in a data science role, with a proven track record ofdeveloping and deploying impactful machine learning models in a production environment. Technical Expertise: Expert proficiency in Python and SQL. Deep understanding of machine learning algorithms (e.g., regression, classification, clustering, NLP) and statistical modeling. Hands-on experience with machine learning libraries and frameworks such as Scikit-learn, TensorFlow, or PyTorch. Experience with big data technologies (e.g., Spark, BigQuery) and cloud platforms (GCP, AWS). Strategic Mindset: Ability to translate complex business problems into well-defined data science projects and communicate technical concepts effectively to non-technical stakeholders. Leadership: Demonstrated ability to lead projects, mentor junior team members, and collaborate effectively across cross-functional teams. Education: Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline is preferred. Benefits (What We Offer) Work with the Best: Collaborate with top-tier professionals across media, advertising, tech, fashion, lifestyle, and publishing, shaping the future of these dynamic industries. Grow Your Skills: Unlock your potential with access to innovative training programs, immersive workshops, and exclusive industry events. Work-Life Harmony: Enjoy the flexibility of hybrid work, empowering you to balance professional success with personal priorities. Foster Connection & Belonging: Join our Employee Resource Groups and help create a welcoming workplace where everyone feels valued and empowered. Wellness First: Prioritize your well-being with a comprehensive benefits package that includes medical, dental, and vision insurance from Day 1. The base salary for this role is between $149,000-$181,00. The actual base pay offered is dependent upon many factors, such as: transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. Hearst Magazines is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Qualifications Working at Hearst Magazines: Work with the Best: Collaborate with top-tier professionals across media, advertising, tech, fashion, lifestyle, and publishing, shaping the future of these dynamic industries. Grow Your Skills: Unlock your potential with access to innovative training programs, immersive workshops, and exclusive industry events. Work-Life Harmony: Enjoy the flexibility of hybrid work, empowering you to balance professional success with personal priorities. Foster Connection & Belonging: Join our Employee Resource Groups and help create a welcoming workplace where everyone feels valued and empowered. Wellness First: Prioritize your well-being with a comprehensive benefits package that includes medical, dental, and vision insurance from Day 1. Plan for Your Financial Future: Enjoy competitive financial perks, including a 401(k) plan with a generous company match. The base salary for this role is between $149,000 - $181,000. The actual base pay offered is dependent upon many factors, such as: transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. Hearst Magazines is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Job DescriptionAbout Us:Live experiences help people cross today's digital divide and focus on what truly connects us - the here, the now, this once-in-a-lifetime moment that's bringing us together. To fulfill Gametime's mission of uniting the world through shared experiences, we make it easy for people to discover and access the live experiences that matter most.With platforms on iOS, Android, mobile web and desktop supporting more than 60,000 events across the US and Canada, we are reimagining the event ticket industry in order to move at the speed of life.About the Role We're looking for a highly analytical and business-savvy Senior Pricing Data Scientist to join our Pricing Strategy team. In this role, you'll design and execute advanced pricing models, lead experimentation efforts, and uncover insights that power monetization and growth. You'll work cross-functionally with Product, Analytics, Revenue, and Engineering to ensure our pricing strategies are data-driven, rigorously tested, and aligned with customer value. This is a high-impact opportunity for someone who thrives at the intersection of data science, economics, and strategy, and who is passionate about using data to influence pricing, product design, and long-term business outcomes. Key ResponsibilitiesModel Development & Optimization Design, build, and maintain pricing and demand elasticity models using statistical and machine learning methods. Leverage behavioral, transactional, and marketplace data to optimize price points, discount strategies, and product bundling. Develop tools to support scenario modeling, revenue forecasting, and price testing simulations. Experimentation & Testing Design A/B and multivariate experiments to test pricing changes, discount strategies, and offer configurations. Analyze test results with statistical rigor, including significance testing, confidence intervals, and causal inference techniques. Partner with experimentation platform owners to automate and scale pricing experiments across channels and customer segments. Insight Generation & Strategy Support Conduct in-depth analyses of customer willingness to pay, price sensitivity, and competitor pricing strategies. Deliver insights on monetization opportunities, marketplace dynamics, and revenue optimization levers. Partner with strategy and product teams to develop recommendations based on model outputs and empirical evidence. Cross-functional Collaboration Collaborate closely with Product Managers, Engineers, and Revenue teams to embed pricing intelligence into user experiences. Translate complex technical findings into actionable business recommendations for stakeholders across the org. Contribute to roadmap planning, strategic decision-making, and post-launch pricing reviews. What You BringRequired Qualifications 5+ years of experience in data science, pricing analytics, or quantitative strategy roles. Advanced proficiency in Python or R, SQL, and statistical modeling techniques. Strong experience with A/B testing frameworks and causal inference methods (e.g., regression, matching, difference-in-differences). Solid understanding of pricing theory, elasticity modeling, and optimization. Skills & Attributes Excellent problem-solving and critical thinking skills; able to distill ambiguity into structured analyses. Business-oriented mindset with the ability to prioritize impact and communicate clearly with non-technical audiences. Self-starter with a passion for experimentation and continuous improvement. Preferred Degree in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative discipline (Master's or PhD preferred). Experience in a consumer-facing marketplace, e-commerce, or SaaS environment. Familiarity with tools such as Looker, Amplitude, dbt, or in-house experimentation platforms. Why This Role Matters Your work will help define how we price, scale, and monetize our products. By bringing science and experimentation to our pricing approach, you'll directly impact revenue growth, customer satisfaction, and strategic decision-making. What We can Offer: Flexible PTO Competitive salary & equity package Monthly Gametime credits for any event ($1,200/yr) Medical, dental, & vision insurance Life insurance and disability benefits Diverse Family-forming benefits through Carrot Fertility 401k, HSA, pre-tax savings programs Company off-sites and meet-ups Wellness programs Tenure recognition At Gametime pay ranges are subject to change and assigned to a job based on specific market median of similar jobs according to 3rd party salary benchmark surveys. Individual pay within that range can vary for several reasons including skills/capabilities, experience, and available budget. United States - Pay Range$140,718-$165,550 USD Gametime is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone can thrive, feel a sense of belonging, and do great work together. As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, veteran status, sex, parental status, gender identity or expression, transgender status, sexual orientation, national origin, age, disability or genetic information. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our company.

Patreon is a media and community platform where over 300,000 creators give their biggest fans access to exclusive work and experiences. We offer creators a variety of ways to engage with their fans and build a lasting business including: paid memberships, free memberships, community chats, live video, and selling to fans directly with one-time purchases. Ultimately our goal is simple: fund the creative class. And we're leaders in that space, with: $10 billion+ generated by creators since Patreon's inception 100 million+ free memberships for fans who may not be ready to pay just yet, and 25 million+ paid memberships on Patreon today. We're continuing to invest heavily in building the best creator platform with the best team in the creator economy and are looking for a Senior Data Scientist to support our mission. This role is based in New York or San Francisco and open to those who are able to be in-office 2 days per week on a hybrid work model. About the Role You'll work in lock step with your cross-functional team to build product features that help creators improve their membership monetization. You'll conduct quantitative research to inform product strategy and opportunities, design metrics to help track goals and make decisions, devise learning methods (including experiments) to test hypotheses, and work closely with our machine learning and data engineering teams on building MVP user-facing data products. You'll translate data into actionable insights and communicate your technical work to the data team, your cross-functional partners, executive leadership, and the rest of the company. You'll be a cultural and technical leader on the data science team. About You Bachelor's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience. You have a wealth of experience helping product teams make great decisions with data. You are an experimentation expert and possess a very strong statistical inference skillset. You have solid analytical thinking. You ask the right questions and strive to see beyond the numbers to understand what an analysis represents in terms of real-world applications. You have experience making tradeoffs between speed and accuracy. You are a SQL expert and have experience in Python or R to perform statistical analyses. You have a track record of building strong relationships with product, engineering, research, and design teammates. You have a growth mindset and aspire to continuously improve your soft and technical skills. You are an expert communicator with a love for clarity and simplicity. About Patreon Patreon powers creators to do what they love and get paid by the people who love what they do. Our team is passionate about making this mission and our core values come to life every day in our work. Through this work, our Patronauts: Put Creators First | They're the reason we're here. When creators win, we win. Build with Craft | We sign our name to every deliverable, just like the creators we serve. Make it Happen | We don't quit. We learn and deliver. Win Together | We grow as individuals. We win as a team. We hire talented and passionate people from different backgrounds because workplace diversity and inclusion is critical to our ability to serve creators worldwide. If you're excited about a role but your past experience doesn't match with every bullet point outlined above, we strongly encourage you to apply anyway. If you're a creator at heart, are energized by our mission, and share our company values, we'd love to hear from you. Patreon is proud to be an equal opportunity employer. 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CompStak is a pioneer in crowdsourced commercial real estate (CRE) data and analytics. Our platform transforms raw lease, sales, and property data into actionable insights for brokers, lenders, landlords, and investors. As we expand our data products, the scale and sophistication of our data pipelines and analytical systems are critical to delivering reliable, timely, and high-quality insights to our customers. Location: New York, NY (Hybrid- Three days per week in the office, subject to change) We are seeking an Applied Data Scientist - Econometrics with a strong foundation in economics, econometrics, finance, or commercial real estate and an interest in applying quantitative modeling to real-world market behavior. This role is ideal for someone who understands how markets work, has experience working with data, and wants to apply (and grow) modern analytical and data science methods within a commercial real estate context.In this role, you will help shape how CompStak analyzes, models, and interprets market dynamics by combining domain expertise with econometric and quantitative techniques. Your mission is to:-Apply econometric and statistical modeling to analyze and forecast trends in commercial real estate and related economic drivers.-Learn and apply modern analytical and machine learning techniques as needed to enhance insights and support CompStak's data products.-Build scalable workflows that integrate structured CRE datasets with new, unstructured sources to support data enrichment and automation.-Collaborate closely with engineering, product, and data teams to develop data-driven solutions.-Bridge domain knowledge and quantitative methods to deliver models that are accurate, interpretable, and meaningful for business decisions.Responsibilities Develop econometric and predictive models: Use quantitative methods to identify patterns, forecast trends, and interpret economic relationships in CRE markets. Build and optimize data workflows: Create and refine data ingestion and transformation pipelines for structured and unstructured commercial real estate datasets. Ensure data quality: Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability. Communicate insights: Translate complex quantitative analysis into clear, actionable insights for both technical and non-technical stakeholders. Stay current: Keep up with developments in econometrics, applied analytics, and trends in CRE markets and data science. Skills & Experience 3+ years of experience in an econometrics-focused or analytical role (e.g., economics research, finance, market analysis, consulting, commercial real estate, or corporate strategy). Strong understanding of econometrics, applied statistics, and quantitative modeling, demonstrated through academic or professional experience. Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost). Experience working with large or complex datasets and using data to study market dynamics. Excellent organizational, communication, and stakeholder management skills. Bonus: Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., Hugging Face, LangChain, PyTorch/TensorFlow). Bonus: Experience working in commercial real estate, PropTech, or investment analytics. Total Compensation range: $120,000 - $160,000 About CompStak Launched in 2012, we've built a network of over 30,000 brokers, appraisers and research professionals across the country, using a unique crowdsourced model. Our clients enjoy the foremost lease and sale transaction data combined with a robust analytics platform. CompStak's unique data and intuitive platform is used by the world's largest real estate investors, lenders, brokers and appraisers to compare properties, underwrite investments and loans, close deals and track market trends. CompStak has over 100 team members in the US and overseas; and we continue to grow. We're backed by top VCs and industry players like Morgan Stanley, Canaan Partners, IA Capital, Transamerica, Moody's, RealPage, 500 Startups, and Daily Mail Group, and have raised over $75m to date. Our HQ is in New York City, we have regional offices in Atlanta, Chicago and Los Angeles, and we have an international office in Belgrade, Serbia. We pride ourselves on an environment that is fun, collaborative, and rewards hard work. We look forward to the value that future employees will add to our amazing teams! CompStak is an equal opportunity employer that celebrates employees and applicants of all identities, backgrounds, abilities, and perspectives. We foster a welcoming work environment that supports diversity and inclusion, and we reject discrimination or harassment of any individual. If you are a person with a disability and require assistance with any part of the application process, please let us know. All employment decisions are made on the basis of qualifications, merit, and business need.

Current is a leading U.S. fintech serving people who have been overlooked by traditional banks. We are one of the fastest-growing companies with nearly 4 million members. Headquartered in NYC, our results-driven environment empowers our team to build better products, grow faster, and have a direct impact on our mission to improve financial outcomes for our members. About the Role At Current, data is at the core of everything we do. As a Senior Data Scientist on the Data and Growth teams, you will focus on machine learning modeling to build predictive models that help us understand our customers better, improve user experience, and efficiently acquire and retain members. This is a hands-on role focused on solving complex problems, developing and deploying ML models, and driving data-driven decision-making. Your day-to-day will involve analyzing, preparing, and structuring data; building and optimizing predictive models; leveraging clustering algorithms; and collaborating with cross-functional teams (Product, Engineering, Marketing) to integrate ML solutions into customer-focused strategies and processes. Responsibilities Design, develop, and deploy predictive classification and regression models, along with anomaly detection models and algorithms. Conduct extensive EDA, feature engineering, and data preprocessing to ensure high-quality input for ML models. Evaluate and optimize model performance using statistical and ML techniques. Design and execute A/B tests to measure and validate model impact. Perform customer segmentation using various clustering techniques. Develop and implement model monitoring dashboards and establish model governance techniques. Collaborate with Analytics, Product, Engineering, and Marketing teams to seamlessly integrate predictive models into workflows. Work with the ML Engineering team to ensure efficient data pipelines and scalable model deployment. Analyze diverse datasets to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation. Qualifications About You 5+ years of experience in data science with a strong emphasis on machine learning modeling. Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch. Expertise in SQL and working with large, complex structured and semi-structured datasets. Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods. Experience in feature engineering, model selection, and performance optimization. Experienced in designing, executing, analyzing, and reporting on experiments. Strong communication skills and ability to present findings to technical and non-technical stakeholders. Master's or higher degree in Data Science, Computer Science, Statistics, or a related field is preferred. Preferred Skills & Qualifications Experience working in fintech, e-commerce, or other data-rich consumer-facing industries. Familiarity with Google Cloud Platform (GCP) services, particularly Vertex AI and Dataflow, for scalable data processing and model training. Experience with dbt for data modeling. Familiarity with BigQuery or other MPP (Massively Parallel Processing) databases. Experience using the Scala programming language for developing scalable and efficient data pipelines. Benefits Competitive salary Stock options 401(k) savings plan Discretionary performance bonus program Biannual performance reviews Medical, Dental and Vision premiums covered at 100% for you and your dependents Unlimited time off and paid holidays Generous parental leave policy Commuter benefits Healthcare and Dependent care FSA benefit Employee Assistance Programs focused on mental health Healthcare advocacy program for all employees Access to mental health apps Team building activities Our modern Chelsea-based office with open floor plan, stocked kitchen, and catered lunches This role has a base salary range of $170,000.00 - $220,000.00. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits.