Data scientist jobs in Paterson, NJ

Your work will change lives. Including your own. Please note: Our offices will be closed for our annual winter break from December 22, 2025, to January 2, 2026. Our response to your application will be delayed. The Impact You'll Make As a member of Recursion's AI-driven drug discovery initiatives, you will be at the forefront of reimagining how biological knowledge is generated, stored, accessed, and reasoned upon by LLMs. You will play a key role in developing the biological reasoning infrastructure, connecting large-scale data and codebases with dynamic, agent-driven AI systems.You will be responsible for defining the architecture that grounds our agents in biological truth. This involves integrating biomedical resources to enable AI systems to reason effectively and selecting the most appropriate data retrieval strategies to support those insights. This is a highly collaborative role: you will partner with machine learning engineers, biologists, chemists, and platform teams to build the connective tissue that allows our AI agents to reason like a scientist. The ideal candidate possesses deep expertise in both core bioinformatics/cheminformatics libraries and modern GenAI frameworks (including RAG and MCP), a strong architectural vision, and the ability to translate high-potential prototypes into scalable production workflows. In this role, you will: * Architect and maintain robust infrastructure to keep critical internal and external biological resources (e.g., ChEMBL, Ensembl, Reactome, proprietary assays) up-to-date and accessible to reasoning agents. * Design sophisticated context retrieval strategies, choosing the most effective approach for each biological use case, whether working with structured, entity-focused data, unstructured RAG, or graph-based representations. * Integrate established bioinformatics/cheminformatics libraries into a GenAI ecosystem, creating interfaces (such as via MCP) that allow agents to autonomously query and manipulate biological data. * Pilot methods for tool use by LLMs, enabling the system to perform complex tasks like pathway analysis on the fly rather than relying solely on memorized weights. * Develop scalable, production-grade systems that serve as the backbone for Recursion's automated scientific reasoning capabilities. * Collaborate cross-functionally with Recursion's core biology, chemistry, data science and engineering teams to ensure our biological data and the reasoning engines are accurately reflecting the complexity of disease biology and drug discovery. * Present technical trade-offs (e.g., graph vs. vector) to leadership and stakeholders in a clear, compelling way that aligns technical reality with product vision. The Team You'll Join You'll join a bold, agile team of scientists and engineers dedicated to building comprehensive biological maps by integrating Recursion's in-house datasets, patient data, and external knowledge layers to enable sophisticated agent-based reasoning. Within this cross-functional team, you will design and maintain the biological context and data structures that allow agents to reason accurately and efficiently. You'll collaborate closely with wet-lab biologists and core platform engineers to develop systems that are not only technically robust but also scientifically rigorous. The ideal candidate is curious about emerging AI technologies, passionate about making biological data both machine-readable and machine-understandable, and brings a strong foundation in systems biology, biomedical data analysis, and agentic AI systems. The Experience You'll Need * PhD in a relevant field (Bioinformatics, Cheminformatics, Computational Biology, Computer Science, Systems Biology) with 5+ years of industry experience, or MS in a relevant field with 7+ years of experience, focusing on biological data representation and retrieval. * Proficiency in utilizing major public biological databases (NCBI, Ensembl, STRING, GO) and using standard bioinformatics/cheminformatics toolkits (e.g., RDKit, samtools, Biopython). * Strong skills in designing and maintaining automated data pipelines that support continuous ingestion, transformation, and refresh of biological data without manual intervention. * Ability to work with knowledge graph data models and query languages (e.g., RDF, SPARQL, OWL) and translate graph-structured data into relational or other non-graph representations, with a strong judgment in evaluating trade-offs between different approaches. * Competence in building and operating GenAI stacks, including RAG systems, vector databases, and optimization of context windows for large-scale LLM deployments. * Hands-on expertise with agentic AI frameworks (e.g., MCP, Google ADK, LangChain, AutoGPT) and familiarity with leading LLMs (e.g., Google Gemini/Gemma) in agentic workflows, including benchmarking and evaluating agent performance on bioinformatics/cheminformatics tasks such as structure prediction, target identification, and pathway mapping. * Strong Python skills and adherence to software engineering best practices, including CI/CD, Git-based version control, and modular design. * Excellent cross-functional communication skills, ability to clearly explain complex architectural decisions to both scientific domain experts and technical stakeholders. Nice to Have * Strong background in machine learning and deep learning, including hands-on experience with foundation models and modern neural architectures. * Fine-tuning LLMs on scientific corpora for domain-specific reasoning. * Integrating LLMs with experimental or proprietary assay data in live scientific workflows. * Background in drug discovery and target identification. * Meaningful contributions to open-source libraries, research codebases, or community-driven tools. Working Location & Compensation: This is an office-based, hybrid role in either our Salt Lake City, UT or New York City, NY offices. Employees are expected to work in the office at least 50% of the time. At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $200,600 - $238,400. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. #LI-DNI The Values We Hope You Share: * We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. * We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action. * We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection. * We move with urgency because patients are waiting. Speed isn't about rushing but about moving the needle every day. * We take ownership and accountability. Through ownership and accountability, we enable trust and autonomy-leaders take accountability for decisive action, and teams own outcomes together. * We are One Recursion. True cross-functional collaboration is about trust, clarity, humility, and impact. Through sharing, we can be greater than the sum of our individual capabilities. Our values underpin the employee experience at Recursion. They are the character and personality of the company demonstrated through how we communicate, support one another, spend our time, make decisions, and celebrate collectively. More About Recursion Recursion (NASDAQ: RXRX) is a clinical stage TechBio company leading the space by decoding biology to radically improve lives. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously generate one of the world's largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale - up to millions of wet lab experiments weekly - and massive computational scale - owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine. Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in Toronto, Montréal, New York, London, Oxford area, and the San Francisco Bay area. Learn more at ****************** or connect on X (formerly Twitter) and LinkedIn. Recursion 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, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation. Accommodations are available on request for candidates taking part in all aspects of the selection process. Recruitment & Staffing Agencies: Recursion Pharmaceuticals and its affiliate companies do not accept resumes from any source other than candidates. The submission of resumes by recruitment or staffing agencies to Recursion or its employees is strictly prohibited unless contacted directly by Recursion's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Recursion, and Recursion will not owe any referral or other fees. Our team will communicate directly with candidates who are not represented by an agent or intermediary unless otherwise agreed to prior to interviewing for the job.

Duties: Responsible for identifying key metrics and conducting in-depth analyses to guide business and inform strategy decisions. Work with cross-functional teams including Product, Sales, Marketing, Account Management, and Risk to help upsell and cross-sell products and to help improve our merchants' experience. Partner with leaders across the business of Sales, Marketing, Finance and Account Management to deliver high-impact analytics. Identify and define a business challenge and craft a strategic analysis plan to uncover the necessary insights and solutions. Collaborate with leaders, various internal teams and stakeholders across the company to develop insights and analytics solutions for both internal and external clients. Examine diverse data sources and develop statistical models to pinpoint trends and key factors, supporting decision-making in product development, sales strategies, risk management, and operational processes. Build data visualization by leveraging existing tools or developing new ones, as well as providing ongoing enhancements to business dashboards. Implement processes and build tools to make data access, extraction, and analysis more efficient. Build and grow relationships with internal teams to proactively identify business needs and address them using analytics. QUALIFICATIONS: Minimum education and experience required: Master's degree in Business Analytics, Data Science, Machine Learning, or related field of study plus 4 years (48 months) of experience in the job offered or as Data Scientist, Decision Analytics Associate, or related occupation. Skills Required: This position requires four (4) years of experience with the following: Using Python to conduct complex analyses to solve unstructured problems via building predictive models using libraries NumPy, Pandas, Scikit-learn, Scipy, and Statsmodels; predictive modeling techniques, including Logistic Regression and Decision Trees; unsupervised learning using K-Means clustering and elbow method; model interpretability via SHAP; Microsoft Excel (VBA, Vlookup, Index Match, Pivot Tables). This position requires two (2) years of experience with the following: Customer Churn Predictive Models with supervised learning techniques leveraging XGBoost, Random Forest, and time series forecasting methods ARIMA, Prophet, and LSTM using libraries TensorFlow, Keras, Fbprophet; anomaly detection methods, including Isolation Forest and One-Class SVM; Statistical Analysis and Hypothesis Testing capabilities, including ANOVA and TURF Analysis; handling banking-related datasets, including Customer Complaints Data and Payments Data; Financial Scenario Analysis and Risk Modeling using Monte Carlo simulations and scenario analysis; Dashboard creation and automation using Looker, Tableau, and Power BI; Advanced SQL, including writing CTE, Windows Functions, and Stored Procedures; data pipelines leveraging Cron Jobs, Shell Scripts, and Python Automation; Log parsing and text processing using PERL; Data integration with Java backends via REST APIs; KPI tracking and reporting automation by integrating Python, SQL, and BI tools; Jupyter Notebooks for data analysis and visualization; Streaming and deployment with Apache Kafka and Docker. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set, and location. For those in eligible roles, discretionary incentive compensation which may be awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. In addition, please visit: ******************************************** Job Location: 545 Washington Blvd, Jersey City, NJ 07310. Full-Time. Salary: $173,945 to $210,000 per year.

Job Description Mirage is the leading AI short-form video company. We're building full-stack foundation models and products that redefine video creation, production and editing. Over 20 million creators and businesses use Mirage's products to reach their full creative and commercial potential. We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you'll have an opportunity to have an outsized impact on our products and our company's culture. Our Products Captions Mirage Studio Our Technology AI Research @ Mirage Mirage Model Announcement Seeing Voices (white-paper) Press Coverage TechCrunch Lenny's Podcast Forbes AI 50 Fast Company Our Investors We're very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. ** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) We do not work with third-party recruiting agencies, please do not contact us** About the Role: As a member of our Data Science staff, you'll own end-to-end measurement by defining north-star metrics, architecting rigorous experiments, and converting insights into roadmap-shaping decisions. You'll partner with Product, Design, and Engineering to elevate instrumentation and data quality and deliver quantified recommendations that improve activation, engagement, retention, and revenue. Key Responsibilities: Lead analysis and exploration to uncover trends in product and user behavior and prioritize the highest leverage opportunities Design and evaluate rigorous A/B tests and set success criteria and power and guardrails and deliver clear post experiment readouts Collaborate with cross functional leaders to define core metrics and establish data driven goals for product experimentation Develop and maintain analytical models and reproducible pipelines that support full funnel analytics Apply statistical techniques to identify patterns and opportunities in large datasets and quantify expected impact and risk Create executive ready visualizations and dashboards that drive alignment and action among stakeholders Embed with designers and engineers to guide instrumentation and ensure data informed decisions throughout the product lifecycle Provide recommendations to improve user experience and conversion and overall product performance and track realized impact Stay current on industry trends and emerging technologies in analytics and introduce pragmatic improvements to tools and methods Requirements: 5+ years as a data scientist or in a similar role with a focus on product analytics High proficiency in SQL and either Python or R for data manipulation, analysis, and modeling Expertise in statistical analysis, hypothesis testing, and experimental design for A/B testing and product experimentation In-depth knowledge of data visualization tools and techniques to effectively communicate insights and storytelling Strong analytical thinking and problem-solving skills, with the ability to translate complex data into actionable recommendations Strong written and verbal communication skills and the ability to partner with cross-functional teams to build a great business Bonus Points: Master's or PhD in a quantitative field (Statistics, Mathematics, Computer Science, or related) Full-funnel analytics experience, including data collection, cleaning, transformation, analysis, and performance measurement Familiarity with modern data warehousing and large-scale data processing; comfortable working with very large datasets and distributed computing frameworks Benefits: Comprehensive medical, dental, and vision plans 401K with employer match Commuter Benefits Catered lunch multiple days per week Dinner stipend every night if you're working late and want a bite! Grubhub subscription Health & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc) Multiple team offsites per year with team events every month Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $160K - $220K

Data Scientist NYC Private Equity - Investment Management Firm J Harlan Group is currently conducting a search for an experienced and highly motivated Data Scientist, at a prominent NYC Private Equity - Investment Manager. An exciting opportunity to join this fast-growing and dynamic investment organization that is experiencing exceptional growth! The Data Scientist will play a critical role in driving data-driven decision-making across the firm's investment strategies, portfolio management, and risk platform. The ideal candidate will bring extensive experience in data science, investment management/strategies and an understanding of portfolio management & risk management. Key Responsibilities: Working in a Hybrid work environment: You will work closely with verticals, business intelligence analysts, data engineers, and other stakeholders to design, develop and deploy data-driven solutions that drive investment decisions and facilitate improved operational outcome at their portfolio companies. You will have the opportunity to bring your ideas to life by building on a foundation of strong internal support, clear vision, engaged users and bright, kind teammates. Analytical Insights: Conduct in-depth analysis of internal or portfolio company data for deep understanding of underlying linear (and non-linear) dynamical structures. Data Analysis and Modeling: Develop and apply advanced statistical, machine learning and artificial intelligence models in collaboration with internal stakeholders to provide novel insights into operational and investment issues. Risk Analysis and Management: Work closely risk team to develop and apply data-driven risk models ML Ops: Collaborate with data engineers and engineers to design and implement data pipelines, design infrastructure, and enable continuous delivery of high-performing models in production. Product Management: Work with vertical teams and portfolio company users to identify and concisely describe issues to solve, and subsequently translate and document these in terms of scope and functional requirements. Collaboration and Communication: Work closely with cross-functional teams, enabling clear communication and broad understanding of models applied and interpretation of results. Innovation and Best Practices: Stay up to date with emerging trends, technologies and methodologies in data science, machine learning, artificial intelligence, and quantitative analysis. The ideal candidate would have a background including: Minimum of 3-7 years of experience in Data Science, preferably with experience with the analysis or application of data in finance or economics - specific experience with real assets a plus! Strong theoretical background in and practical experience with optimization, statistical techniques, and machine learning & artificial intelligence models Strong programming skills in Python (or R or Julia) and SQL Extensive experience with standard machine learning libraries (e.g., in Python; Numpy, Pandas, SciPy, Scikit-Learn, PyTorch, TPOT, etc.) Cloud Platform: Familiarity with cloud-based business intelligence and data analytics platforms (e.g., Azure, AWS, GCP) - and associated ML platforms (e.g., SageMaker, Vertex) Working knowledge bringing models to production Experience with data modeling, data warehousing, and ELT processes Strong analytical, strategic thinking, and problem-solving skills. Excellent communication and interpersonal skills, with the ability to interact effectively with senior management and external stakeholders. Nice to Have: Monte Carlo Simulation: Experience building Monte Carlo models for time series simulation; experience with VAR or similar a plus. Domain Expertise: Experience with the analysis or application of data in finance or economics - specific experience with real assets a plus Education: Strong academic record and a bachelor's or higher degree in relevant STEM field (e.g., Physics, Mathematics, Data Science, Computer Science). An individual who loves working with deep and complex financial problems and wants to have an outsized impact with the products and solutions they deliver. An individual with a passion for data science, high level of intellectual curiosity, a commitment to excellence and an unparalleled drive to deliver world-class services. About the Client: The firm is a leading investment manager and private equity firm specializing in the acquisition of transportation equipment and asset operating platforms in the infrastructure sector. The firm targets real asset investment opportunities that are cash yielding with downside protection, and benefit from a team with deep, longstanding relationships and financial and operating expertise. Today, the firm manages over $9bn of assets globally across rail, intermodal, aviation, and emerging technology strategies with office locations in NYC, Chicago and St. Louis. They seek candidates who are high-energy self-starters who want to join an investment management firm on the leading edge of financial markets. The management team needs individuals of the highest professional caliber who are leaders, problem solvers, analytic, detail-oriented, and entrepreneurial. Everyone at the firm works side-by-side with the firm's senior partners in a highly collaborative and charged investment environment. Successful candidates are: Analytic and relentless in pursuit of the right answer Strong communicators who excel at rapid synthesis Able to demonstrate sound business judgment Able to digest complexity while maintaining an understanding of the “big picture” of business needs Team players who are energized by a collaborative enterprise The firm's employees maintain the highest professional and ethical standards. The firm has earned a reputation for honesty, fair dealing, and transparency in a competitive industry. They believe that these standards are the foundation for superior investment performance and are critical to delivering performance to clients. The estimated salary range is $135,000-$215,000. Employees may also be eligible for an annual discretionary incentive compensation award. Actual base salary may vary based upon, but not limited to relevant skills, experience, qualifications, and geographic location.

:" Our roster has an opening with your name on it FanDuel is looking for a Data Scientist, to drive our Sportsbook customer generosity distribution and bonus spend optimization. In this role you will be responsible for customer segmentation, modeling, automation, reporting and data analysis across all areas of Sportsbook generosity distribution. Using your numerical and technology capabilities you will play a key role in bonus spend research, optimization and communication of results to CRM and Commercial senior management. This is a great opportunity for somebody who wants to work in an environment where curiosity is rewarded, and people are empowered to make decisions. The ideal candidate will have a passion for continual learning and developing innovative solutions to business problems. THE GAME PLAN Everyone on our team has a part to play * Take on data science projects from start to finish, including working with stakeholders to agree project KPIs, and reporting on progress and outcomes throughout projects at agreed cadence * Deliver high-quality analysis, customer segmentation and predictive models which help drive incremental revenue through optimal automated bonus spend distribution * Improve our understanding of customer behaviors, efficiency of promotions, and effectiveness of bonus spend * Through idea generation and exploratory analysis, develop new and innovative ways to turn behaviors into features for use in analysis, segmentation and predictive modeling * Create, modify, and evolve models which solve business problems, and show demonstrable improvements to department KPIs * Demonstrate accurate insights and predictions using easy to interpret visualizations and clear explanations of results, recommendations, methods, biases and limitations * Work with Data Engineering and Analytics Engineer to optimize data quality and data modeling pipelines * Take responsibility to learn the necessary skills and techniques, to develop ability to work with independence, integrity and accuracy * Collaborate with key stakeholders to help in identifying areas for improvement, and support their strategic objectives * Assist in coaching, developing and performance managing less experienced team members * Contribute new ideas for data science projects which have demonstrable potential to improve revenue performance or customer experience THE STATS What we're looking for in our next teammate * Minimum of 3+ years of previous Data Science or Analytics Experience * Minimum 1+ years building and deploying complex machine learning models with real world applications * Have a developed technical skill set which facilitates high-quality, efficient & comprehensive quantitative analysis * Proficient in SQL and experience of manipulating large datasets in Microsoft Excel * Proficient in statistical or programming software and techniques (e.g. in Python, R, C#, VBA, etc.) * Strong communication and presentation skills, experienced in explaining technical projects to non-technical stakeholders * Experience working with data visualization tools like Tableau an advantage * Undergraduate degree in a numerate or technical discipline * Interest in sports is a plus * Interest or experience in the Sports betting industry is an advantage ABOUT FANDUEL FanDuel Group is the premier mobile gaming company in the United States. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America's #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry's unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product. In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states and Puerto Rico. The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company's affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia. FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT). PLAYER BENEFITS We treat our team right We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level. FanDuel is an equal opportunities employer and we believe, as one of our principles states, "We are One Team!". As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or another other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included. The applicable salary range for this position is $116,000 - $145,000 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws. #LI-Hybrid "}

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.

Title Principal Predictive Modeler/Data Scientist - Insurance Analytics - NJ #2811 Company is seeking a Principal Predictive Modeler / Data Scientist. This is a senior-level technical position. Rapidly growing unit aims to design, create and offer innovative data-driven products to the property and casualty insurance as well as life insurance and parts of the credit industry. You will apply your highly developed analytical skills to work on all aspects of the insurance value chain, ranging from pricing models, fraud detection, process triaging, and financial risk models to a variety of other analytics solutions. You will also communicate with customers, external partners and internal departments while effectively leading complex analytics projects. Independently executes data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and sales support. Utilizes advanced statistical techniques to create high-performing predictive models and creative analyses to address business objectives and client needs. Demonstrates to internal and external customers how analysis can be implemented to maximize business strategies including cost benefit analyses. Provides technical sales support, which may include providing strategic consulting, needs assessments and the preparation and presentation of analytical proposals. Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions. Creates clear and easy to understand reports and/or PowerPoint decks for client meetings or third party collaborations. Verbally presents analysis ideas, progress and results to internal managers, external partners and customers. Communicates with internal groups on data specifications and with IT engineers on model/algorithm implementation. Provides high quality ongoing customer and sales support; uncovering opportunities, answering questions, resolving problems and building solutions. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects. Shares knowledge within the analytics group. Required qualifications: Graduate-level degree with concentration in a quantitative discipline such as statistics computer science, mathematics, economics, or operations research OR Bachelor's degree with CAS Associate or Fellow status or substantial exam progress. Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal groups (data, IT, product and sales) as well as third-party partners and customers (insurance companies). 8+ years of relevant work experience including 3 years of statistical modeling and data mining in a P&C insurance context (insurance company or insurance consulting firm) using large and complex datasets. Experience with personal lines rating plan modeling is a strong plus. Life or health insurance experience is a bonus. Expertise in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models, cluster analysis, principal components, and feature creation, validation. Programming experience with SAS (STAT, macros, EM), R and other statistical software (CART, Emblem, SPSS, Matlab). Greenplum and UNIX experience is a plus. Aptitude in performing multiple tasks and dealing with changing deadline requirements. This includes knowing when to escalate issues. Maintains a focused, flexible, organized, and proactive manner. Proficiency in Microsoft Office (Excel, Word, PowerPoint). Not just software use but proficiency in creating effective and visually appealing PowerPoint presentations, and well-structured error-free and readable spreadsheets. Bottom line requirements we need notes on with candidate submittal: 1. Graduate degree with concentration in a quantitative discipline or Bachelor's degree with CAS Associate or Fellow status. 2. 8+ years of relevant work experience including 3 years of statistical modeling and data mining in a Property and Casualty Insurance context (insurance company or insurance consulting firm). 3. Expertise in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models, cluster analysis, principal components, and feature creation, validation. 4. Programming experience with SAS (STAT, macros, EM), R and other statistical software (CART, Emblem, SPSS, Matlab). Greenplum and UNIX experience is a plus. Additional Information All your information will be kept confidential according to EEO guidelines.

Job Description We are looking for a talented Data Scientist skilled in Python and SQL. In this role, you will analyze large datasets, develop predictive models, and derive actionable insights that will guide business decisions. Requirements Proven experience as a Data Scientist or a similar role, with a strong focus on data analysis and modeling. Proficiency in programming languages, especially Python, and strong SQL skills for database management and querying. Experience with statistical analysis techniques and data visualization tools (e.g., Tableau, Matplotlib, Seaborn). Familiarity with machine learning frameworks and libraries (e.g., Scikit-learn, TensorFlow). Strong analytical skills and the ability to work with large datasets to extract meaningful information. Experience in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving abilities and strong communication skills to present findings effectively. A degree in Computer Science, Mathematics, Statistics, or a related field is preferred. Benefits About Us We specialize in Digital, ERP, and larger IT Services. We offer flexible, efficient and collaborative solutions to any organization that requires IT, experts. Our agile, agnostic, and flexible solutions will help you source the IT Expertise you need. If you are looking for new opportunities, send your profile at ***************************. Also follow our LinkedIn page for new job opportunities and more. Zone IT Solutions is an equal opportunity employer and our recruitment process focuses on essential skills and abilities. We encourage applications from a diverse array of backgrounds, including individuals of various ethnicities, cultures, and linguistic backgrounds, as well as those with disabilities.

Roles and Responsibilities Introduction As a Data Scientist at Rantodac, you will help transform our clients' data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it's investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live. Your Role and Responsibilities As an Advisory Data Scientist, you will demonstrate expertise in Advanced people analytics. We use the latest advanced analytics technologies, tools, and techniques to extract insights from our data. We work collaboratively with other teams within the company and apply these insights to make complex and strategic decisions for the benefit of Rantodac. As a Data Scientist, you'll team with some of the best mind in the industry to create innovative world class solutions focused on business needs. You'll do this by designing/developing analytical approaches to solve our client's business problems. Responsibilities: Work with clients in defining the key business problems to be solved while developing, maintaining and leveraging key client relationships. Identifying, gathering, and analyzing complex, multi-dimensional datasets utilizing a variety of tools. Designing Advanced Analytics solutions and services in the area(s) of optimization (linear, mixed integer, constraint programming) or simulations, or predictive analytics. Formulating mathematical approaches to solve those problems potentially utilizing ILOG CPLEX, Standard Query Language (SQL), Apache Spark, Statistical Packages Social Sciences(SPSS), Python, R. Using industry technologies, tools and data mining frameworks for data analytics including data visualization for analyzing and drawing conclusions. Communicating the data insights to key stakeholders and get their buy-ins. Integrating the analytics Into existing business work flows. Measuring business outcome (quantitatively and/or qualitatively) on a periodic basis. Developing junior team members and leading project tasks. Maintaining knowledge and understanding of current and emerging trends within the analytics industry. A good level of business acumen and business domain knowledge is highly preferred Required Technical and Professional Expertise A minimum of 0-2 years of experience in determining mathematical approaches to solve problems, sampling plan and gathering/ analyzing /portraying data Proficient in designing/building/managing solutions utilizing for example ILOG CPlex, Python, Standard Query Language (SQL), Apache Spark, Statistical Package Social Sciences(SPSS), or R Work experience in building predictive models using various ML algorithms, drawing insights from the model output, communicating the results to key stakeholders, integrating the analytics into existing business workflows and measuring business outcome Expertise in statistical analysis and deploying the results of the analysis Experience in data collection/ data mining/text mining Preferred Technical and Professional Expertise A minimum of 0-3 years experience in determining mathematical approaches to solve problems, sampling plan and gathering/ analyzing /portraying data Exposure to unstructured data sets and Natural Language Processing Proven Business acumen and business domain knowledge is highly preferred

Implify, Inc is a Global IT Solutions and services firm. Since it's inception, Implify, Inc has been providing best-quality and cost-effective IT solutions to fortune 1000 companies, mid-range companies and upcoming companies via its onsite, Offshore and in-house service models. IMPLIFY is an IT consulting services and software development firm dedicated to business success through long-term relationships with our clients and staff. IMPLIFY has built a dynamic, profitable, service-oriented enterprise, and is positioned to successfully respond to trends and changes in the information technology industry. Job Description Data Scientist Location: Newark NJ Interview process: Phone and In Person (face to face) Job Descripction As a Data Scientist, you solve complex challenges and identify new opportunities using a combination of analytical expertise, business acumen, strategic thinking, and project and relationship management skills. This is an exciting opportunity to be a part of a new strategic initiative & this position is located in Newark, N.J., a quick, easy 15-minute train ride from New York Penn Station. RESPONSIBILITIES • Integrate and mine large data sets, connecting data from disparate sources to identify insights and patterns using predictive and prescriptive analytics, and machine learning techniques • Conduct intermediate and advanced statistical analysis, such as linear regression, ANOVA, time-series analysis, classification models, neural networks, decision trees, as well as analysis of unstructured data (e.g., social media listening, digital footprints, speech analytics) • Prepare and present written and verbal reports, findings, and presentations to key stakeholders, distilling complex statistical information into easy-to-understand business language • Apply knowledge of U.S. businesses and corporate groups and relevant industry knowledge to analysis and insights • Manage project budgets and timelines, ensuring times and on-budget completion QUALIFICATIONS • Experience analyzing large data sets using statistical software, such as SAS, R, Python, and SPSS, to discover new business insights • Excel and PowerPoint a must. SQL Programming and experience of at least one DBMS such as IBM DB2, Oracle, SQL Server or Sybase are required. Java strongly desired • Prior experience with building models, analyzing unstructured data, and/or machine learning • Relevant academic experience and work experience in Statistics, with exposure to data structures and data visualization • Master's degree in Mathematics, Statistics, Engineering, Computer Science, or a quantitative discipline plus a minimum of 2-3 years of work experience, or bachelor's degree plus 5 years work experience • Well-developed written and oral communication skills, with ability to present and explain data to business manager • Strong project management skills / experience managing projects, budgets, and schedules to successful completion • Some prior exposure to financial services or insurance industry desired Additional Information All your information will be kept confidential according to EEO guidelines.

Voleon Securities, a new business within the Voleon Group, provides liquidity in securities markets. We apply state-of-the-art AI/ML techniques to construct our liquidity-provision strategies. For more than a decade, our affiliate Voleon Capital Management has led the hedge fund industry and worked at the frontier of applying AI/ML to investment management, becoming a multibillion-dollar asset manager. Voleon Securities builds on Voleon's deep real-world experience applying ML to financial markets. We are seeking an entrepreneurial Technical Lead in Data Science who is excited to get in on the ground floor of a growing securities business. Data is at the heart of everything we do-from modeling and strategy development to production monitoring and compliance. As we expand our data-driven investment initiatives, we are seeking a Technical Lead in Data Science to guide the design, implementation, and evolution of our analytical systems and mentor a growing team of data scientists. As a Technical Lead - Data Science, you will provide technical direction and management fora team of data scientists working on high-impact problems across trading and research systems. You will be responsible for shaping analytical frameworks, ensuring methodological rigor, and delivering insights that inform business and research decisions. You will collaborate with stakeholders in engineering, research, and leadership while driving innovation and excellence in our data science practice. Responsibilities Collaborate with Technical Product Owners in Research and Engineering to define priorities, scope solutions, and deliver actionable insights to stakeholders. Own investigations of complex production behaviors and design robust methods for identifying, analyzing, and communicating system anomalies. Mentor and manage junior and mid-level data scientists; provide architectural oversight for data projects. Serve as a technical authority within the data science function, set standards for data quality, statistical rigor, and reproducibility. Lead the design, development, and deployment of analytical pipelines to monitor and interpret production behavior across trading and research systems, ensuring its correctness. Champion best practices in data governance, tooling, and collaborative development (CI/CD, version control, code reviews). Drive continual growth and learning within the team by onboarding new Data Scientists, growing teams, and fostering a culture of curiosity, collaboration, and applied experimentation. Requirements Master's degree or higher in a quantitative, technical, or analytical field such as Data Science, Statistics, Computer Science, Engineering, Finance, or an MBA with strong analytical training. 3+ years of experience managing data scientists, including responsibility for performance development, technical direction, and project execution. Demonstrated ability to lead cross-functional data initiatives, translate business objectives into analytical goals, and ensure timely delivery. Strong understanding of data science fundamentals, including statistical analysis, data preparation, root cause investigation, and the proven ability to guide others' work in these areas. Familiarity with data tooling and workflows (e.g., SQL, Pandas, R, Airflow), with enough fluency to review and support technical contributors effectively. Basic software development skills and experience with bash, linux/unix, and git Experience communicating complex findings to executive and technical stakeholders, including presenting insights, tradeoffs, and recommendations. Track record of establishing scalable methodologies, driving technical standards, and fostering collaboration in fast-paced, analytically rigorous environments. Preferred Experience building or growing high-performing data science teams in production-aware or high-stakes settings. Exposure to financial markets, trading systems, or quantitative research environments. Familiarity with production monitoring systems, data quality pipelines, or analytics platform development. 7+ years of experience managing data scientists. Experience managing a large team or multiple teams. “Friends of Voleon” Candidate Referral Program If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms, and conditions, please review the Voleon Referral Bonus Program. Equal Opportunity Employer The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law. We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

SonSoft Inc. is a USA based corporation duly organized under the laws of the Commonwealth of Georgia. SonSoft Inc is growing at a steady pace specializing in the fields of Software Development, Software Consultancy, and Information Technology Enabled Services. Job Description As a Data Scientist, you solve complex challenges and identify new opportunities using a combination of analytical expertise, business acumen, strategic thinking, and project and relationship management skills. This is an exciting opportunity to be a part of a new strategic initiative & this position is located in Newark, N.J., a quick, easy 15-minute train ride from New York Penn Station. Occasional domestic travel may be required. Responsibilities:- Integrate and mine large data sets, connecting data from disparate sources to identify insights and patterns using predictive and prescriptive analytics, and machine learning techniques Conduct intermediate and advanced statistical analysis, such as linear regression, ANOVA, time-series analysis, classification models, neural networks, decision trees, as well as analysis of unstructured data (e.g., social media listening, digital footprints, speech analytics) Prepare and present written and verbal reports, findings, and presentations to key stakeholders, distilling complex statistical information into easy-to-understand business language Apply knowledge of U.S. businesses and corporate groups and relevant industry knowledge to analysis and insights Manage project budgets and timelines, ensuring times and on-budget completion. Qualifications Experience analyzing large data sets using statistical software, such as SAS, R, Python, and SPSS, to discover new business insights Excel and PowerPoint a must. SQL Programming and experience of at least one DBMS such as IBM DB2, Oracle, SQL Server or Sybase are required. Java strongly desired Prior experience with building models, analyzing unstructured data, and/or machine learning Relevant academic experience and work experience in Statistics, with exposure to data structures and data visualization Master's degree in Mathematics, Statistics, Engineering, Computer Science, or a quantitative discipline plus a minimum of 2-3 years of work experience, or bachelor's degree plus 5 years work experience Well-developed written and oral communication skills, with ability to present and explain data to business manager Strong project management skills / experience managing projects, budgets, and schedules to successful completion Some prior exposure to financial services or insurance industry desired Additional Information Connect with me at ******************************************* ( For Direct Clients Requirements ) ** U.S. Citizens and those who are authorized to work independently in the United States are encouraged to apply. We are unable to sponsor at this time. Note:- This is a Full-Time & Permanent job opportunity for you. Only US Citizen, Green Card Holder, GC-EAD, H4-EAD & L2-EAD can apply. No OPT-EAD, H1B & TN candidates, please. Please mention your Visa Status in your email or resume. ** All your information will be kept confidential according to EEO guidelines.

Valence has built the only AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance and support to any leader or employee. We're not just talking about the future of work - we're building it now, with the most innovative Fortune 500 companies across healthcare, financial services, manufacturing, and technology. Our focus is on the problems that actually decide whether AI changes how organizations operate - the ones with no playbook, no obvious answers, and no guarantee of success. If you want to be part of the small group that defines how AI transforms the future at a global scale, this is your chance. And this isn't for everyone. We're not looking for people who want predictability or incremental progress. We only want those who are restless at the edge of what's possible, who get bored when things feel “done,” and who are driven to redefine what AI can mean for leaders, companies, and the world. Because at Valence, the work worth doing is the kind that redefines work itself. The RoleIn this role you'll be critical in shaping how data informs decisions across our product, customer, and go-to-market teams. You'll uncover user behavior patterns, operational performance insights, and commercial opportunities - all while helping to lay the foundation for a scalable, insight-driven data culture. You'll collaborate deeply with leaders across Product, Engineering, Sales, and Customer Success to ensure we're making the smartest possible decisions from day one. About ValenceWe're the only company pioneering leadership coaching for large enterprises in an AI-first way. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together through AI-powered personalization that adapts to individual goals and organizational culture using the latest advances in machine learning and natural language processing. We've been featured in Harvard Business Review, TIME, World Economic Forum, Financial Times, Forbes and an Inc. 5000 fastest-growing private companies in America. Our clients represent the most diverse and sophisticated enterprise AI implementations globally, including Coca-Cola, Delta, Nestlé, General Mills, Schneider Electric, Deutsche Telekom, AstraZeneca, Prudential, CVS and Bristol Myers Squibb. Working at Valence means you'll work directly with Fortune 500 technology leaders, building expertise through the most complex enterprise deployments while gaining insight into diverse organizational approaches to AI transformation. These aren't just any enterprise clients - they're the companies defining what AI-first business transformation looks like across every major industry.What You'll Do Product & Customer Analytics You will analyze platform usage, feature engagement, and user interaction with our AI-powered coaching tools to surface actionable insights. You'll identify friction points and areas of opportunity across key user journeys. You'll support rigorous A/B testing, evaluate AI model performance, and help assess the impact of new features on user experience and outcomes. Reporting & Visualization You'll develop self-serve dashboards and recurring reporting frameworks to democratize access to data across teams. You will translate complex data into clear, compelling stories for technical and non-technical audiences to support data-informed decision-making. Data Infrastructure & Collaboration You'll collaborate with Product and Engineering teams to define tracking requirements and ensure accurate, consistent data collection. You'll identify and recommend improvements to data processes that enhance quality, efficiency, and trust in analytics across the organization. What We're Looking For You have 2+ years of experience in a data analytics role, ideally within a B2B SaaS or AI-focused startup environment. You hold at least a Bachelor's degree in Data Science, Statistics, Computer Science, Economics, or a related quantitative field. You are highly proficient in SQL and comfortable writing complex queries and working with diverse database structures. You have hands-on experience with Python (using libraries like Pandas, NumPy, Matplotlib, or Seaborn) or R for data analysis and visualization. You're familiar with BI tools such as Tableau, Looker, Power BI, or equivalent platforms. You're familiar with using Excel or Google Sheets for ad hoc analysis and data exploration. You may also bring experience with product analytics platforms (e.g., Mixpanel, Amplitude), cloud environments (e.g., AWS or GCP), or data warehousing concepts. You know how to break down complex business problems into structured analyses. You are skilled at identifying trends, patterns, and outliers in data to uncover key insights. You can clearly communicate findings-both in writing and verbally-to technical and non-technical stakeholders alike. Nice to have: You've worked in a fast-paced, early-stage startup, you bring familiarity with AI/ML concepts, you understand SaaS metrics and enterprise customers. What you'll get Ownership & Rapid Growth Outsized missions from day one, with direct responsibility for company-defining projects Work alongside the executive team with transparency into strategy and decision-making Influence on direction through real-time customer feedback and market insights AI-First Operator Work directly with cutting-edge AI models and next-generation platforms Build expertise in enterprise AI implementation across Fortune 500 companies and multiple industries Establish yourself as a recognized leader among peers in shaping how AI transforms work at a global scale Compensation Competitive salary including base + bonuses Comprehensive health coverage (medical, dental, vision) from day one Generous PTO, company-wide R&R shutdowns, and paid parental leave Retirement plan support for US and global employees Equity Meaningful ownership in a venture-backed company at a growth inflection point Financial upside that comes from scaling fast Top-up grants as we scale and you deliver exceptional performance - your compensation grows alongside your impact Top-Performing Culture A culture built for top talent: intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together Learn more about us and meet our team here Location and Work EnvironmentThis role is 3 days a week (Tues - Thursday) minimum in office in Toronto or NYC depending on your residency. Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions. Diversity and InclusionWe are dedicated to creating a diverse and inclusive environment where everyone feels valued and supported. We encourage applications from candidates of all backgrounds and offer accommodations upon request throughout the hiring process. If you have any questions, please reach out to Allison Langille, Head of People, at [email protected].We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Bachelors or Master's degree with specialization in Computer Science, Information Systems, Mathematics, Statistics or other quantitative disciplines Excellent ability to query large datasets using SQL queries and working with databases Excellent in programming languages such as Java, Python, etc. Experience in data extraction and processing, using MapReduce, Pig, Hive, etc. Proficient programming skills using SAS and/or R Knowledge of building and applying machine learning or predictive modeling Strong problem solving skills Exceptional ability to communicate and present findings clearly to both technical and non-technical audiences Excellent interpersonal and collaboration skills Additional Information Thanks & Regards, Praveen K. Paila ************

Job Description About the Role As a Data Scientist, you'll bring deep technical rigor to how data is analyzed, tested, and applied across the business. You'll design and interpret experiments, apply advanced statistical methods, and build scalable analytical frameworks that directly inform product strategy and company performance. You'll work across Engineering and Product to establish robust measurement practices, expand the use of data-driven decision making, and uncover insights that shape Decagon's trajectory. This role blends strong analytical expertise with product acumen and the ability to influence at the highest levels. & In this role, you will Conduct deep-dive analyses using advanced statistical methods on user behavior, product performance, and business outcomes to surface actionable insights. Enhance and extend data models, metrics, and dashboards to ensure consistent, scalable reporting across teams. Design, implement, and analyze controlled A/B test experiments to measure product changes and customer experience. Collaborate with Product and Engineering to embed experimentation and measurement best practices into product development cycles. Build and continuously improve Decagon's data stack, ensuring scalable models, pipelines, and tools that empower self-serve analytics across the company. Communicate findings clearly and persuasively to executives and cross-functional stakeholders, influencing strategic decision-making. Evaluate and interpret the performance of ML models (e.g., classification, recommendation, LLM-based systems), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions. Be the primary driver of experimentation culture at Decagon, helping define how we design, measure, and scale experiments across the business. & What We're Looking For Strong ability to structure ambiguous problems, translate them into analytical approaches, and deliver business impact through data. Advanced proficiency in SQL and Python, with a solid foundation in statistics and experimental design. 5+ years (or equivalent experience) in data science or product analytics roles, ideally within high-scale consumer or marketplace products. Ability to reason about and analyze machine learning models, understanding their assumptions, trade-offs, and impact on product and customer outcomes. A proven track record of designing, running, and analyzing experiments at scale. Excellent communication skills, with experience influencing stakeholders and driving decisions across teams.

Job Description The Financial Crime Data Scientist combines investigative expertise with advanced data science techniques to identify, assess, and mitigate financial risks, fraud, and emerging cyber-enabled threats. This role will analyze transactional, behavioral, and device-level signals; detect indicators of compromise; identify anomalous activity; and support intelligence integration into Appgate's Fraud security products. The analyst will collaborate closely with internal product teams and other external intelligence sources to track financial crime patterns (e.g., ransomware operators, malware families, account takeover trends, money mule networks) and translate insights into predictive models, detection rules, and automated workflows. This candidate bridges fraud investigation, data analysis, and technical implementation while working cross-functionally with Product, Engineering, Risk, Marketing, and Operations. Responsibilities Fraud & Threat Intelligence Conduct in-depth investigations into financial crime activity, including transaction fraud, account compromise, synthetic identity, malware-enabled fraud, and ransomware monetization patterns. Monitor intelligence feeds for emerging threat actors, TTPs, botnet activity, phishing kits, malware variants, and monetization schemes. Identify fraud indicators, behavioral patterns, anomalies, and signal correlations across structured and unstructured data sources. Data Analytics & Modeling Collect, clean, engineer, and analyze large datasets using Python, SQL, and cloud-based data platforms. Perform statistical analysis, clustering, anomaly detection, and supervised/unsupervised machine learning to improve predictive fraud scoring. Build prototypes for fraud detection algorithms; partner with data science teams to productionize models. Data Engineering & Automation Build and maintain analytical data pipelines with engineers using tools such as Airflow, dbt, Spark, or similar. Automate data ingestion (APIs, logs, intelligence feeds, enrichment sources) for ongoing fraud monitoring. Create dashboards and visualizations using Tableau, Power BI, Looker, Mode, or similar to communicate findings. Cross-Functional Intelligence Integration Translate fraud intelligence into actionable requirements for product and engineering teams (e.g., detection rules, model features, new risk signals). Collaborate with marketing and customer-facing teams to prepare intelligence briefs, threat summaries, and fraud trend reports. Produce fraud loss metrics, risk scoring insights, and performance evaluations of prevention tools. Security & Compliance Maintain strict confidentiality and follow handling protocols for sensitive data, PII, and regulated financial information. Stay current on fraud trends, sanctions, AML regulations, and industry standards. Required Qualifications Bachelors/Masters degree in Data Science, Applied Statistics, Digital Forensics, Financial Engineering, Criminology, Computer Science, Cybersecurity, or relevant field; or equivalent experience. 1-3+ years in fraud detection, threat intelligence, financial crime investigations, cyber threat analysis, or risk operations. Strong proficiency in: SQL for data extraction and manipulation Python (pandas, NumPy, scikit-learn) for data analysis Data visualization tools (Tableau, Power BI, Looker, etc.) Familiarity with machine learning concepts, anomaly detection, statistics, and predictive modeling. Experience with fraud platforms, case management systems, device intelligence, or behavioral analytics systems. Demonstrated investigative mindset with excellent documentation and communication skills. Preferred / Nice-to-Have Technical Skills Experience with big data technologies (Spark, Databricks, Snowflake). Knowledge of fraud-specific data sources: device fingerprinting, behavioral biometrics, geolocation, IP intelligence, OSINT, malware intel feeds. Familiarity with malware families, attack chains, and cyber threat intelligence frameworks such as MITRE ATT&CK. Exposure to API-based integrations, data enrichment pipelines, and log analysis. Understanding of risk scoring systems, rules engines, or real-time decisioning platforms. Experience with AML, KYC, BSA, sanctions screening, or cryptocurrency tracing tools. Key Competencies Analytical and critical thinking Statistical and machine learning literacy Effective communication and storytelling with data Investigative rigor and attention to detail Cross-functional collaboration Integrity and confidentiality Strong problem-solving and decision-making skills Appgate is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. In furtherance of Appgate's policy regarding affirmative action and equal employment opportunity, Appgate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.

We are looking for a data scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. Responsibilities Selecting features, building and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods Extending company's data with third party sources of information when needed Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results in a clear manner Creating automated anomaly detection systems and constant tracking of its performance

Job Description: AI Task Evaluation & Statistical Analysis Specialist We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). Key Responsibilities Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations Dimension Analysis: Analyze performance variations across finance sub-domains, file types, and task categories Reporting & Visualization: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities Quality Framework: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings Stakeholder Communication: Present insights to data labeling experts and technical teams Required Qualifications Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets AI/ML Familiarity: Understanding of LLM evaluation methods and quality metrics Tools: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL Preferred Qualifications Experience with AI/ML model evaluation or quality assurance Background in finance or willingness to learn finance domain concepts Experience with multi-dimensional failure analysis Familiarity with benchmark datasets and evaluation frameworks 2-4 years of relevant experience

At Fun.xyz, we believe a tokenized future is a beneficial inevitability, granting financial emancipation to everyone with an internet connection. For a blockchain-first global economy to exist, value exchange must become intuitive, secure, and seamless. Enter Checkout - the highest converting payment solution in web3. By integrating Checkout, dApps enable users to complete any on-chain action using crypto from a wallet, centralized exchange, or on-ramped fiat from a card or bank account. With access to market-leading routing and their asset portfolio at the point of sale, users are faster, stickier, and more engaged. For dApps, Checkout scales their user acquisition potential without launching new chains or integrating multiple third party providers. We built Checkout because we envision a world where anyone, anywhere, can purchase anything with any asset. If that sounds like a vision you can get behind, we want to hear from you. Role Overview We're looking for a Data Scientist to supercharge our data-driven strategy and ensure we're building the right things at the right time. You'll be embedded in the heart of our product and engineering teams, shaping insights that guide strategy, uncover user behavior, and optimize execution across Fun.xyz. This role is perfect for someone who thrives in fast-paced, ownership-driven environments, loves solving open-ended problems, and is excited about the potential of blockchain data.Responsibilities Design and build scalable data models to analyze transaction flows and user behavior Support the optimization of data transformations, pipelines, and workflows Work directly with the CFO to provide insights on the business' performance Maintain data quality, observability, and reproducibility across analytical systems Partner with engineers and product teams to deliver actionable, production-grade insights Run experiments, apply causal inference, and drive evidence-based product decisions Translate complex data into clear stories for both technical and non-technical stakeholders Requirements Proficiency in Python and SQL (5+ years) Strong background in statistical analysis, experimentation, and causal inference Familiar with analyzing end-user behavior for optimization (A/B testing, conversion rates, etc.) Skilled in modern data platforms (Redshift, Snowflake, Databricks, etc.) and orchestration/transformation tools (dbt or similar) Deep curiosity about crypto, DeFi, on-chain data, and Web3 infrastructure Nice To Have Experience analyzing large-scale transaction or financial datasets Hands-on experience with ML/AI libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow) Familiarity with market dynamics (spreads, slippage, liquidity, etc.) A track record of thriving in ownership-heavy, fast-moving environments A problem-solving approach that blends rigor, creativity, and first-principles thinking We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.