Data scientist jobs in New York

Please apply here: ************************************************************************************* Senior Data Scientist, Agentic AI This is a potential contract to hire role. About the Role: Our client is transforming into a modern, data-driven insurance company. As part of this journey, we're looking for a Senior Data Scientist to help build and scale advanced Agentic AI and LLM-based solutions that automate workflows, improve decision-making, and enhance customer experience. You'll work closely with senior leaders and cross-functional teams to design AI systems that drive measurable business impact. This is a high-visibility role within company's Data Science Lab (DSL) - a hub for innovation, rapid testing, and operationalizing AI solutions across the enterprise. What You'll Do Design and deploy Agentic AI solutions to automate complex business processes. Operationalize LLMs and Generative AI for unstructured data (contracts, claims, medical records, customer interactions). Build intelligent agents and reasoning systems that integrate with core business platforms. Partner with data engineering and AIOps teams to scale AI models from prototype to production. Translate AI research into real-world solutions for underwriting, claims, customer service, and risk assessment. Define use cases, measure ROI, and collaborate with business stakeholders. Mentor junior data scientists and help standardize AI/ML frameworks across the organization. What You Bring PhD + 2 years OR Master's + 4 years of relevant AI/ML experience. 3+ years of hands-on experience in AI model development. Strong foundation in probability, statistics, and machine learning. Proficiency in Python, PyTorch, TensorFlow, and LangGraph. Proven experience deploying scalable AI solutions. Excellent communication skills and ability to work cross-functionally with Product, Engineering, and Business teams. Leadership experience in mentoring and guiding data scientists.

My name is Bill Stevens, and I have a new three month plus contract to hire Senior Data Scientist Agentic AI opportunity available for a major firm with offices located in Midtown, Manhattan on the West Side and Holmdel, New Jersey that could be of interest to you, please review my specification below and I am available at any time to speak with you so please feel free to call me. The work week schedule will be hybrid, three days a week in either of the firms' offices and two days remote. The onsite work site will be determined by the candidate. The ideal candidate should also possess a green card or be of citizenship. No Visa entanglements and no H1-B holding company submittals. The firms Data & AI team spearheads a culture of intelligence and automation across the enterprise, creating business value from advanced data and AI solutions. Their team includes data scientists, engineers, analysts, and product leaders working together to deliver AI-driven products that power growth, improve risk management, and elevate customer experience. The firm created the Data Science Lab (DSL) to reimagine emerging technologies, evolving consumer needs, and rapid advances in AI. The DSL expedites transition to data-driven decision making and fosters innovation by rapidly testing, scaling, and operationalizing state-of-the-art AI. We are seeking a Senior Data Scientist Engineer, Agentic AI who is an experienced individual contributor with deep expertise in AI/ML and a track record of turning advanced research into practical, impactful enterprise solutions. This role focuses on building, deploying, and scaling agentic AI systems, large language models, and intelligent automation solutions that reshape how the firm operates, serves customers, and drives growth. You'll collaborate directly with senior executives on high-visibility projects to bring next-generation AI to life across the firm's products and services. Key Responsibilities: Design and deploy Agentic AI solutions to automate complex business workflows, enhance decision-making, and improve customer and employee experiences. Operationalize cutting-edge LLMs and generative AI to process and understand unstructured data such as contracts, claims, medical records, and customer interactions. Build autonomous agents and multi-step reasoning systems that integrate with the firm's core platforms to deliver measurable business impact. Partner with data engineers and AIOps teams to ensure AI models are production-ready, scalable, and robust, from prototype to enterprise deployment. Translate research in agentic AI, reinforcement learning, and reasoning into practical solutions that support underwriting, claims automation, customer servicing, and risk assessment. Collaborate with product owners, engineers, and business leaders to define use cases, design solutions, and measure ROI. Contribute to the Data Science Lab by establishing repeatable frameworks for developing, testing, and deploying agentic AI solutions. Mentor junior data scientists and contribute to the standardization of AI/ML practices, tools, and frameworks across the firm. You are: Passionate about pushing the frontier of AI while applying it to solve real-world business problems. Excited by the potential of agentic AI, autonomous systems, and LLM-based solutions to transform industries. A hands-on builder who thrives on seeing AI solutions move from proof-of-concept to real-world deployment. Comfortable working in multi-disciplinary teams and engaging with senior business leaders to align AI solutions with enterprise goals. You have: PhD with 2+ years of experience OR have a Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field 3+ years of hands-on AI modeling/development experience Strong theoretical foundations in probability & statistics Strong programming skills in Python including PyTorch, Tensorflow, LangGraph Solid background in machine learning algorithms, optimization, and statistical modeling Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level Excellent analytical and problem-solving abilities with superb attention to detail Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success This position pays $150.00 per hour on a w-2 hourly basis or $175.00 per hour on a Corp basis. The Corp rate is for independent contractors only and not third-party firms. No Visa entanglements and no H1-B holding companies. The interview process will include an initial phone or virtual interview screening. Please let me know your interest in this position, availability to interview and start for this position along with a copy of your recent resume or please feel free to call me at any time with any questions. Regards Bill Stevens Senior Technical Recruiter PRI Technology Denville, New Jersey 07834 ************** ******************************

Godel Terminal is a cutting edge financial platform that puts the world's financial data at your fingertips. From Equities and SEC filings, to global news delivered in milliseconds, thousands of customers rely on Godel every day to be their guide to the world of finance. We are looking for a senior engineer in New York City to join our team and help build out live data services as well as historical data for US markets and international exchanges. This position will specifically work on new asset classes and exchanges, but will be expected to contribute to the core architecture as we expand to international markets. Our team works quickly and efficiently, we are opinionated but flexible when it's time to ship. We know what needs to be done, and how to do it. We are laser focused on not just giving our customers what they want, but exceeding their expectations. We are very proud that when someone opens the app the first time they ask: “How on earth does this work so fast”. If that sounds like a team you want to be part of, here is what we need from you: Minimum qualifications: Able to work out of our Manhattan office minimum 4 days a week 5+ years of experience in a financial or startup environment 5+ years of experience working on live data as well as historical data 3+ years of experience in Java, Python, and SQL Experience managing multiple production ETL pipelines that reliably store and validate financial data Experience launching, scaling, and improving backend services in cloud environments Experience migrating critical data across different databases Experience owning and improving critical data infrastructure Experience teaching best practices to junior developers Preferred qualifications: 5+ years of experience in a fintech startup 5+ years of experience in Java, Kafka, Python, PostgreSQL 5+ years of experience working with Websockets like RXStomp or Socket.io 5+ years of experience wrangling cloud providers like AWS, Azure, GCP, or Linode 2+ years of experience shipping and optimizing Rust applications Demonstrated experience keeping critical systems online Demonstrated creativity and resourcefulness under pressure Experience with corporate debt / bonds and commodities data Salary range begins at $150,000 and increases with experience Benefits: Health Insurance, Vision, Dental To try the product, go to *************************

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets. Our challenge We are looking for a candidate will be responsible for designing, implementing, and managing data solutions on the Azure platform in Financial / Banking domain. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within New York City, NY is $130k - $140k/year & benefits (see below). The Role Responsibilities: Lead the development and optimization of batch and real-time data pipelines, ensuring scalability, reliability, and performance. Architect, design, and deploy data integration, streaming, and analytics solutions leveraging Spark, Kafka, and Snowflake. Ability to help voluntarily and proactively, and support Team Members, Peers to deliver their tasks to ensure End-to-end delivery. Evaluates technical performance challenges and recommend tuning solutions. Hands-on knowledge of Data Service Engineer to design, develop, and maintain our Reference Data System utilizing modern data technologies including Kafka, Snowflake, and Python. Requirements: Proven experience in building and maintaining data pipelines, especially using Kafka, Snowflake, and Python. Strong expertise in distributed data processing and streaming architectures. Experience with Snowflake data warehouse platform: data loading, performance tuning, and management. Proficiency in Python scripting and programming for data manipulation and automation. Familiarity with Kafka ecosystem (Confluent, Kafka Connect, Kafka Streams). Knowledge of SQL, data modelling, and ETL/ELT processes. Understanding of cloud platforms (AWS, Azure, GCP) is a plus. Domain Knowledge in any of the below area: Trade Processing, Settlement, Reconciliation, and related back/middle-office functions within financial markets (Equities, Fixed Income, Derivatives, FX, etc.). Strong understanding of trade lifecycle events, order types, allocation rules, and settlement processes. Funding Support, Planning & Analysis, Regulatory reporting & Compliance. Knowledge of regulatory standards (such as Dodd-Frank, EMIR, MiFID II) related to trade reporting and lifecycle management. We offer: A highly competitive compensation and benefits package. A multinational organization with 58 offices in 21 countries and the possibility to work abroad. 10 days of paid annual leave (plus sick leave and national holidays). Maternity & paternity leave plans. A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region). Retirement savings plans. A higher education certification policy. Commuter benefits (varies by region). Extensive training opportunities, focused on skills, substantive knowledge, and personal development. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms. A flat and approachable organization. A truly diverse, fun-loving, and global work culture. S YNECHRON'S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

DL Software produces Godel, a financial information and trading terminal. Role Description This is a full-time, on-site role based in New York, NY, for a Data Engineer. The Data Engineer will design, build, and maintain scalable data systems and pipelines. Responsibilities include data modeling, developing and managing ETL workflows, optimizing data storage solutions, and supporting data warehousing initiatives. The role also involves collaborating with cross-functional teams to improve data accessibility and analytics capabilities. Qualifications Strong proficiency in Data Engineering and Data Modeling Mandatory: strong experience in global financial instruments including equities, fixed income, options and exotic asset classes Strong Python background Expertise in Extract, Transform, Load (ETL) processes and tools Experience in designing, managing, and optimizing Data Warehousing solutions

Are you a data engineer who loves building systems that power real impact in the world? A fast growing healthcare technology organization is expanding its innovation team and is looking for a Data Engineer II to help build the next generation of its data platform. This team sits at the center of a major transformation effort, partnering closely with engineering, analytics, and product to design the foundation that supports advanced automation, AI, intelligent workflows, and high scale data operations that drive measurable outcomes for hospitals, health systems, and medical groups. In this role, you will design, develop, and maintain software applications that process large volumes of data every day. You will collaborate with cross functional teams to understand data requirements, build and optimize data models, and create systems that ensure accuracy, reliability, and performance. You will write code that extracts, transforms, and loads data from a variety of sources into modern data warehouses and data lakes, while implementing best in class data quality and governance practices. You will work hands on with big data technologies such as Hadoop, Spark, and Kafka, and you will play a critical role in troubleshooting, performance tuning, and ensuring the scalability of complex data applications. To thrive here, you should bring strong problem solving ability, analytical thinking, and excellent communication skills. This is an opportunity to join an expanding innovation group within a leading healthcare platform that is investing heavily in data, AI, and the future of intelligent revenue operations. If you want to build systems that make a real difference and work with teams that care deeply about improving patient experiences and provider performance, this is a chance to do highly meaningful engineering at scale.

🚀 Market Data Engineer - New York | Cutting-Edge Trading Environment I'm partnered with a leading technology-driven trading team in New York looking to bring on a Market Data Engineer to support global research, trading, and infrastructure groups. This role is central to managing the capture, normalization, and distribution of massive volumes of historical market data from exchanges worldwide. What You'll Do Own large-scale, time-sensitive market data capture + normalization pipelines Improve internal data formats and downstream datasets used by research and quantitative teams Partner closely with infrastructure to ensure reliability of packet-capture systems Build robust validation, QA, and monitoring frameworks for new market data sources Provide production support, troubleshoot issues, and drive quick, effective resolutions What You Bring Experience building or maintaining large-scale ETL pipelines Strong proficiency in Python + Bash, with familiarity in C++ Solid understanding of networking fundamentals Experience with workflow/orchestration tools (Airflow, Luigi, Dagster) Exposure to distributed computing frameworks (Slurm, Celery, HTCondor, etc.) Bonus Skills Experience working with binary market data protocols (ITCH, MDP3, etc.) Understanding of high-performance filesystems and columnar storage formats

Data Engineer - Data Migration Project 6-Month Contract (ASAP Start) Hybrid - Manhattan, NY (3 days/week) We are seeking a Data Engineer to support a critical data migration initiative for a leading sports entertainment and gaming company headquartered in Manhattan, NY. This role will focus on transitioning existing data workflows and analytics pipelines from Amazon Redshift to Databricks, optimizing performance and ensuring seamless integration across operational reporting systems. The ideal candidate will have strong SQL and Python skills, experience working with Salesforce data, and a background in data engineering, ETL, or analytics pipeline optimization. This is a hybrid role requiring collaboration with cross-functional analytics, engineering, and operations teams to enhance data reliability and scalability. Minimum Qualifications: Advanced proficiency in SQL, Python, and SOQL Hands-on experience with Databricks, Redshift, Salesforce, and DataGrip Experience building and optimizing ETL workflows and pipelines Familiarity with Tableau for analytics and visualization Strong understanding of data migration and transformation best practices Ability to identify and resolve discrepancies between data environments Excellent analytical, troubleshooting, and communication skills Responsibilities: Modify and migrate existing workflows and pipelines from Redshift to Databricks. Rebuild data preprocessing structures that prepare Salesforce data for Tableau dashboards and ad hoc analytics. Identify and map Redshift data sources to their Databricks equivalents, accounting for any structural or data differences. Optimize and consolidate 200+ artifacts to improve efficiency and reduce redundancy. Implement Databricks-specific improvements to leverage platform capabilities and enhance workflow performance. Collaborate with analytics and engineering teams to ensure data alignment across business reporting systems. Apply a “build from scratch” mindset to design scalable, modernized workflows rather than direct lift-and-shift migrations. Identify dependencies on data sources not yet migrated and assist in prioritization efforts with the engineering team. What's in it for you? Opportunity to lead a high-impact data migration initiative at a top-tier gaming and entertainment organization. Exposure to modern data platforms and architecture, including Databricks and advanced analytics workflows. Collaborative environment with visibility across analytics, operations, and engineering functions. Ability to contribute to the foundation of scalable, efficient, and data-driven decision-making processes. EEO Statement: Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

Job title: Lead Software Engineer Duration: Fulltime/Contract to Hire Role description: The successful candidate will be a key member of the HR Technology team, responsible for developing and maintaining global HR applications with a primary focus on HR Analytics ecosystem. This role combines technical expertise with HR domain knowledge to deliver robust data solutions that enable advanced analytics and data science initiatives. Key Responsibilities: Manage and support HR business applications, including problem resolution and issue ownership Design and develop ETL/ELT layer for HR data integration and ensure data quality and consistency Provide architecture solutions for Data Modeling, Data Warehousing, and Data Governance Develop and maintain data ingestion processes using Informatica, Python, and related technologies Support data analytics and data science initiatives with optimized data structures and AI/ML tools Manage vendor products and their integrations with internal/external applications Gather requirements and translate functional needs into technical specifications Perform QA testing and impact analysis across the BI ecosystem Maintain system documentation and knowledge repositories Provide technical guidance and manage stakeholder communications Required Skills & Experience: Bachelor's degree in computer science or engineering with 4+ years of delivery and maintenance work experience in the Data and Analytics space. Strong hands-on experience with data management, data warehouse/data lake design, data modeling, ETL Tools, advanced SQL and Python programming. Exposure to AI & ML technologies and experience tuning models and building LLM integrations. Experience conducting Exploratory Data Analysis (EDA) to identify trends and patterns, report key metrics. Extensive database development experience in MS SQL Server/ Oracle and SQL scripting. Demonstrable working knowledge of tools in CI/CD pipeline primarily GitLab and Jenkins Proficiency in using collaboration tools like Confluence, SharePoint, JIRA Analytical skills to model business functions, processes and dataflow within or between systems. Strong problem-solving skills to debug complex, time-critical production incidents. Good interpersonal skills to engage with senior stakeholders in functional business units and IT teams. Experience with Cloud Data Lake technologies such as Snowflake and knowledge of HR data model would be a plus.

Our client is seeking a Data Engineer with hands-on experience in Web Scraping technologies to help build and scale a new scraping capability within their Data Engineering team. This role will work directly with Technology, Operations, and Compliance to source, structure, and deliver alternative data from websites, APIs, files, and internal systems. This is a unique opportunity to shape a new service offering and grow into a senior engineering role as the platform evolves. Responsibilities Develop scalable Web Scraping solutions using AI-assisted tools, Python frameworks, and modern scraping libraries. Manage the full lifecycle of scraping requests, including intake, feasibility assessment, site access evaluation, extraction approach, data storage, validation, entitlement, and ongoing monitoring. Coordinate with Compliance to review Terms of Use, secure approvals, and ensure all scrapes adhere to regulatory and internal policy guidelines. Build and support AWS-based data pipelines using tools such as Cron, Glue, EventBridge, Lambda, Python ETL, and Redshift. Normalize and standardize raw, vendor, and internal datasets for consistent consumption across the firm. Implement data quality checks and monitoring to ensure the reliability, historical continuity, and operational stability of scraped datasets. Provide operational support, troubleshoot issues, respond to inquiries about scrape behavior or data anomalies, and maintain strong communication with users. Promote data engineering best practices, including automation, documentation, repeatable workflows, and scalable design patterns. Required Qualifications Bachelor's degree in Computer Science, Engineering, Mathematics, or related field. 2-5 years of experience in a similar Data Engineering or Web Scraping role. Capital markets knowledge with familiarity across asset classes and experience supporting trading systems. Strong hands-on experience with AWS services (S3, Lambda, EventBridge, Cron, Glue, Redshift). Proficiency with modern Web Scraping frameworks (Scrapy, BeautifulSoup, Selenium, Playwright). Strong Python programming skills and experience with SQL and NoSQL databases. Familiarity with market data and time series datasets (Bloomberg, Refinitiv) is a plus. Experience with DevOps/IaC tooling such as Terraform or CloudFormation is desirable.

Hey All, We are looking for a mid-level data engineer. No third parties As a result of this expansion, we are seeking experienced software Data engineers with 5+ years of relevant experience to support the design and development of a strategic data platform for SMBC Capital Markets and Nikko Securities Group. Qualifications and Skills • Proven experience as a Data Engineer with experience in Azure cloud. • Experience implementing solutions using - • Azure cloud services • Azure Data Factory • Azure Lake Gen 2 • Azure Databases • Azure Data Fabric • API Gateway management • Azure Functions • Well versed with Azure Databricks • Strong SQL skills with RDMS or no SQL databases • Experience with developing APIs using FastAPI or similar frameworks in Python • Familiarity with the DevOps lifecycle (git, Jenkins, etc.), CI/CD processes • Good understanding of ETL/ELT processes • Experience in financial services industry, financial instruments, asset classes and market data are a plus.

Haptiq is a leader in AI-powered enterprise operations, delivering digital solutions and consulting services that drive value and transform businesses. We specialize in using advanced technology to streamline operations, improve efficiency, and unlock new revenue opportunities, particularly within the private capital markets. Our integrated ecosystem includes PaaS - Platform as a Service, the Core Platform, an AI-native enterprise operations foundation built to optimize workflows, surface insights, and accelerate value creation across portfolios; SaaS - Software as a Service, a cloud platform delivering unmatched performance, intelligence, and execution at scale; and S&C - Solutions and Consulting Suite, modular technology playbooks designed to manage, grow, and optimize company performance. With over a decade of experience supporting high-growth companies and private equity-backed platforms, Haptiq brings deep domain expertise and a proven ability to turn technology into a strategic advantage. The Opportunity As a Data Engineer within the Global Operations team, you will be responsible for managing the internal data infrastructure, building and maintaining data pipelines, and ensuring the integrity, cleanliness, and usability of data across our critical business systems. This role will play a foundational part in developing a scalable internal data capability to drive decision-making across Haptiq's operations. Responsibilities and Duties Design, build, and maintain scalable ETL/ELT pipelines to consolidate data from delivery, finance, and HR systems (e.g., Kantata, Salesforce, JIRA, HRIS platforms). Ensure consistent data hygiene, normalization, and enrichment across source systems. Develop and maintain data models and data warehouses optimized for analytics and operational reporting. Partner with business stakeholders to understand reporting needs and ensure the data structure supports actionable insights. Own the documentation of data schemas, definitions, lineage, and data quality controls. Collaborate with the Analytics, Finance, and Ops teams to build centralized reporting datasets. Monitor pipeline performance and proactively resolve data discrepancies or failures. Contribute to architectural decisions related to internal data infrastructure and tools. Requirements 3-5 years of experience as a data engineer, analytics engineer, or similar role. Strong experience with SQL, data modeling, and pipeline orchestration (e.g., Airflow, dbt). Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). Experience working with REST APIs and integrating with SaaS platforms like Salesforce, JIRA, or Workday. Proficiency in Python or another scripting language for data manipulation. Familiarity with modern data stack tools (e.g., Fivetran, Stitch, Segment). Strong understanding of data governance, documentation, and schema management. Excellent communication skills and ability to work cross-functionally. Benefits Flexible work arrangements (including hybrid mode) Great Paid Time Off (PTO) policy Comprehensive benefits package (Medical / Dental / Vision / Disability / Life) Healthcare and Dependent Care Flexible Spending Accounts (FSAs) 401(k) retirement plan Access to HSA-compatible plans Pre-tax commuter benefits Employee Assistance Program (EAP) Opportunities for professional growth and development. A supportive, dynamic, and inclusive work environment. Why Join Us? We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it. The compensation range for this role is $75,000 to $80,000 USD

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

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable is seeking a product-focused Data Scientist to join our Analytics & Data Science team. In this high-impact role, you'll partner closely with product development teams to transform raw user data into actionable insights that drive growth for Airtable's self-serve business. You'll own critical data pipelines, design and analyze experiments, build dashboards, and deliver strategic insights that inform executive decision-making. This is a unique opportunity to shape the future of a data-driven, AI-native SaaS company and scale analytics best practices across the organization. What you'll do Own and maintain core product data pipelines across DBT, Looker, and Omni, ensuring reliability, scalability, and minimal downtime Build and refine dashboards that deliver self-serve, real-time insights for high-priority product areas Lead the development and delivery of company-wide strategic insights that connect user behavior patterns and inform executive decisions Partner with product and engineering teams to define tracking requirements, implement instrumentation, validate data, and deliver launch-specific dashboards or reports Establish trusted partnerships with product managers, engineers, analysts, and leadership as the go-to resource for product data insights and technical guidance Collaborate with leadership to define the analytics roadmap, prioritize high-impact initiatives, and assess resource needs for scaling product analytics capabilities Mentor junior team members and cross-functional partners on analytics best practices and data interpretation; create documentation and training materials to scale institutional knowledge Support end-to-end analytics for all product launches, including tracking implementation, validation, and post-launch reporting with documented impact measurements Deliver comprehensive strategic analyses or experiments that connect user behavior patterns and identify new growth opportunities Lead or participate in cross-functional projects where data science contributions directly influence product or strategy decisions Migrate engineering team dashboards to Omni or Databricks, enabling self-serve analytics Who you are Bachelor's degree in computer science, data science, mathematics/statistics, or related field 6+ years of experience as a data scientist, data analyst, or data engineer Experience supporting product development teams and driving product growth insight Background in SaaS, consumer tech, or data-driven product environments preferred Expert in SQL and modern data modeling (e.g., dbt, Databricks, Snowflake, BigQuery); sets standards and mentors others on best practices Deep experience with BI tools and modeling (e.g., Looker, Omni, Hex, Tableau, Mode) Proficient with experimentation platforms and statistical libraries (e.g., Eppo, Optimizely, LaunchDarkly, scipy, statsmodels) Proven ability to apply AI/ML tools - from core libraries (scikit-learn, PyTorch, TensorFlow) to GenAI platforms (ChatGPT, Claude, Gemini) and AI-assisted development (Cursor, GitHub Copilot) Strong statistical foundation; designs and scales experimentation practices that influence product strategy and culture Translates ambiguous business questions into structured analyses, guiding teams toward actionable insights Provides thought leadership on user funnels, retention, and growth analytics Ensures data quality, reliability, and consistency across critical business reporting and analytics workflows Experience at an AI-native company, with exposure to building or scaling products powered by AI Knowledge of product analytics tracking frameworks (e.g., Segment, Amplitude, Mixpanel, GA4) and expertise in event taxonomy design Strong documentation and knowledge-sharing skills; adept at creating technical guides, playbooks, and resources that scale team effectiveness Models curiosity, creativity, and a learner's mindset; thrives in ambiguity and inspires others to do the same Crafts compelling narratives with data, aligning stakeholders at all levels and driving clarity in decision-making Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. 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 characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. VEVRAA-Federal Contractor If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants. Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience. Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. To learn more about our comprehensive benefit offerings, please check out Life at Airtable. For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is:$205,200-$266,300 USDFor all other work locations (including remote), the base salary range for this role is:$185,300-$240,000 USD Please see our Privacy Notice for details regarding Airtable's collection and use of personal information relating to the application and recruitment process by clicking here. 🔒 Stay Safe from Job Scams All official Airtable communication will come from an @airtable.com email address. 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About the Team OpenAI's User Operations organization is building the data and intelligence layer behind AI-assisted operations - the systems that decide when automation should help users, when humans should step in, and how both improve over time. Our flagship platform is transforming customer support into a model for "agent-first" operations across OpenAI. About the Role As a Data Scientist on User Operations, you'll design the models, metrics, and experimentation frameworks that power OpenAI's human-AI collaboration loop. You'll build systems that measure quality, optimize automation, and turn operational data into insights that improve product and user experience at scale. You'll partner closely with Support Automation Engineering, Product, and Data Engineering to ensure our data systems are production-grade, trusted, and impactful. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. Why it matters Every conversation users have with OpenAI products produces signals about how humans and AI interact. User Ops Data Science turns those signals into insights that shape how we support users today and design agentic systems for tomorrow. This is a unique opportunity to help define how AI collaboration at scale is measured and improved inside OpenAI. In this role, you will: * Build and own metrics, classifiers, and data pipelines that determine automation eligibility, effectiveness, and guardrails. * Design and evaluate experiments that quantify the impact of automation and AI systems on user outcomes like resolution quality and satisfaction. * Develop predictive and statistical models that improve how OpenAI's support systems automate, measure, and learn from user interactions. * Partner with engineering and product teams to create feedback loops that continuously improve our AI agents and knowledge systems. * Translate complex data into clear, actionable insights for leadership and cross-functional stakeholders. * Develop and socialize dashboards, applications, and other ways of enabling the team and company to answer product data questions in a self-serve way * Contribute to establishing data science standards and best practices in an AI-native operations environment. * Partner with other data scientists across the company to share knowledge and continually synthesize learnings across the organization You might thrive in this role if you have: * 10+ years of experience in data science roles within product or technology organizations. * Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies. * Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation. * Proven experience designing and interpreting experiments and making statistically sound recommendations. * Experience building data systems or pipelines that power production workflows or ML-based decisioning. * Experience developing and extracting insights from business intelligence tools, such as Mode, Tableau, and Looker. * Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks. * Ability to build relationships with diverse stakeholders and cultivate strong partnerships. * Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact. * Ability to operate effectively in a fast-moving, ambiguous environment with limited structure. * Strong communication skills and the ability to translate complex data into stories for non-technical partners. Nice-to-haves: * Familiarity with large language models or AI-assisted operations platforms. * Experience in operational automation or customer support analytics. * Background in experimentation infrastructure or human-AI interaction systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About Gap Inc. Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials. This simple idea-that we all deserve to belong, and on our own terms-is core to who we are as a company and how we make decisions. Our team is made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team. About the Role Gap Inc. is seeking a Principal Data Scientist with deep expertise in operations research and machine learning to lead the design and deployment of advanced analytics solutions across the Product-to-Market (P2M) space. This role focuses on driving enterprise-scale impact through optimization and data science initiatives spanning pricing, inventory, and assortment optimization. The Principal Data Scientist serves as a senior technical and strategic thought partner, defining solution architectures, influencing product and business decisions, and ensuring that analytical solutions are both technically rigorous and operationally viable. The ideal candidate can lead end-to-end solutioning independently, manage ambiguity and complex stakeholder dynamics, and communicate technical and business risk effectively across teams and leadership levels. What You'll Do * Lead the framing, design, and delivery of advanced optimization and machine learning solutions for high-impact retail supply chain challenges. * Partner with product, engineering, and business leaders to define analytics roadmaps, influence strategic priorities, and align technical investments with business goals. * Provide technical leadership to other data scientists through mentorship, design reviews, and shared best practices in solution design and production deployment. * Evaluate and communicate solution risks proactively, grounding recommendations in realistic assessments of data, system readiness, and operational feasibility. * Evaluate, quantify, and communicate the business impact of deployed solutions using statistical and causal inference methods, ensuring benefit realization is measured rigorously and credibly. * Serve as a trusted advisor by effectively managing stakeholder expectations, influencing decision-making, and translating analytical outcomes into actionable business insights. * Drive cross-functional collaboration by working closely with engineering, product management, and business partners to ensure model deployment and adoption success. * Quantify business benefits from deployed solutions using rigorous statistical and causal inference methods, ensuring that model outcomes translate into measurable value * Design and implement robust, scalable solutions using Python, SQL, and PySpark on enterprise data platforms such as Databricks and GCP. * Contribute to the development of enterprise standards for reproducible research, model governance, and analytics quality. Who You Are * Master's or Ph.D. in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics, or a closely related quantitative discipline. * 10+ years of experience developing, deploying, and scaling optimization and data science solutions in retail, supply chain, or similar complex domains. * Proven track record of delivering production-grade analytical solutions that have influenced business strategy and delivered measurable outcomes. * Strong expertise in operations research methods, including linear, nonlinear, and mixed-integer programming, stochastic modeling, and simulation. * Deep technical proficiency in Python, SQL, and PySpark, with experience in optimization and ML libraries such as Pyomo, Gurobi, OR-Tools, scikit-learn, and MLlib. * Hands-on experience with enterprise platforms such as Databricks and cloud environments * Demonstrated ability to assess, communicate, and mitigate risk across analytical, technical, and business dimensions. * Excellent communication and storytelling skills, with a proven ability to convey complex analytical concepts to technical and non-technical audiences. * Strong collaboration and influence skills, with experience leading cross-functional teams in matrixed organizations. * Experience managing code quality, CI/CD pipelines, and GitHub-based workflows. Preferred Qualifications * Experience shaping and executing multi-year analytics strategies in retail or supply chain domains. * Proven ability to balance long-term innovation with short-term deliverables. * Background in agile product development and stakeholder alignment for enterprise-scale initiatives. Benefits at Gap Inc. * Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees. * One of the most competitive Paid Time Off plans in the industry.* * Employees can take up to five "on the clock" hours each month to volunteer at a charity of their choice.* * Extensive 401(k) plan with company matching for contributions up to four percent of an employee's base pay.* * Employee stock purchase plan.* * Medical, dental, vision and life insurance.* * See more of the benefits we offer. * For eligible employees Gap Inc. is an equal-opportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our long-held commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity. Salary Range: $201,700 - $267,300 USD Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible. Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. At Pinterest, Shopping is a strategic initiative that aims to help Pinners take action by surfacing the most relevant content, at the right time, in the best user-friendly way. We do this through a combination of innovative product interfaces, and sophisticated recommendation systems. We are looking for a Staff Data Scientist with experience in machine learning and causal inference to help advance Shopping at Pinterest. In your role you will develop methods and models to explain why certain content is being promoted (or not) for a Pinner. You will work in a highly collaborative and cross-functional environment, and be responsible for partnering with Product Managers and Machine Learning Engineers. You are expected to develop a deep understanding of our recommendation system, and generate insights and robust methodologies to answer the “why”. The results of your work will influence our development teams, and drive product innovation. What you'll do: Ensure that our recommendation systems produce trustworthy, high-quality outputs to maximize our Pinner's shopping experience. Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations. Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners. Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest. Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process. Mentor and up-level junior data scientists on the team. What we're looking for: 7+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data. Strong interest and experience in recommendation systems and causal inference. Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark). Ability to work independently and drive your own projects. Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners. A team player eager to partner with cross-functional partners to quickly turn insights into actions. Bachelor's/Master's degree in a relevant field such as Computer Science, or equivalent experience. In-Office Requirement Statement: We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. Relocation Statement: This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. #LI-REMOTE #LI-NM4 At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only$164,695-$339,078 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data ScientistWho is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The AI Services team is looking for a data scientist with a particular interest in operationalizing and scaling ML/AI applications who is eager to take on the responsibility of contributing to a wide variety of data science projects. The person in this role will be join a team of leading edge data scientists who are not just building models, but are working to solve foundational business problems for the Company. Role In this role you will responsible for: • Designing, developing, and researching ML systems • Studying, transforming, and extending data science prototypes • Searching cleaning, aggregating large data sets from Cloudera, AWS, Azure, Splunk • Application development and maintenance on Linux environments • Performing statistical data analysis • Iteratively training and retraining Machine Learning systems and models • Extending existing ML frameworks and libraries • Data visualization and story telling with Tableau, Jupyter, RShiny and/or d3s • Graph analytics with Python, R or TigerGraph About You • Programming with Python and/or R languages • Programming within ML Frameworks such as TensorFlow, PyTorch, scikit-learn, and/or Spark/ML • Model deployment with containers such as Kubernetes and/or Docker • Anomaly detection and model/data drift analysis affecting production ML models • Building and maintaining ML production pipelines • Solid verbal and written communication skills • Bachelor of Science in Computer Science, Engineering, or Mathematics or similar field • Experience with a Fortune 500 Company a plus #AIMastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard's security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines. In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. Pay Ranges New York City, New York: $166,000 - $265,000 USD

Title: Enterprise Data Management - Data Cloud, Senior Developer I Duration: FTE/Permanent Salary: 130-165k The Data Engineering team oversees the organization's central data infrastructure, which powers enterprise-wide data products and advanced analytics capabilities in the investment management sector. We are seeking a senior cloud data engineer to spearhead the architecture, development, and rollout of scalable, reusable data pipelines and products, emphasizing the creation of semantic data layers to support business users and AI-enhanced analytics. The ideal candidate will work hand-in-hand with business and technical groups to convert intricate data needs into efficient, cloud-native solutions using cutting-edge data engineering techniques and automation tools. Responsibilities: Collaborate with business and technical stakeholders to collect requirements, pinpoint data challenges, and develop reliable data pipeline and product architectures. Design, build, and manage scalable data pipelines and semantic layers using platforms like Snowflake, dbt, and similar cloud tools, prioritizing modularity for broad analytics and AI applications. Create semantic layers that facilitate self-service analytics, sophisticated reporting, and integration with AI-based data analysis tools. Build and refine ETL/ELT processes with contemporary data technologies (e.g., dbt, Python, Snowflake) to achieve top-tier reliability, scalability, and efficiency. Incorporate and automate AI analytics features atop semantic layers and data products to enable novel insights and process automation. Refine data models (including relational, dimensional, and semantic types) to bolster complex analytics and AI applications. Advance the data platform's architecture, incorporating data mesh concepts and automated centralized data access. Champion data engineering standards, best practices, and governance across the enterprise. Establish CI/CD workflows and protocols for data assets to enable seamless deployment, monitoring, and versioning. Partner across Data Governance, Platform Engineering, and AI groups to produce transformative data solutions. Qualifications: Bachelor's or Master's in Computer Science, Information Systems, Engineering, or equivalent. 10+ years in data engineering, cloud platform development, or analytics engineering. Extensive hands-on work designing and tuning data pipelines, semantic layers, and cloud-native data solutions, ideally with tools like Snowflake, dbt, or comparable technologies. Expert-level SQL and Python skills, plus deep familiarity with data tools such as Spark, Airflow, and cloud services (e.g., Snowflake, major hyperscalers). Preferred: Experience containerizing data workloads with Docker and Kubernetes. Track record architecting semantic layers, ETL/ELT flows, and cloud integrations for AI/analytics scenarios. Knowledge of semantic modeling, data structures (relational/dimensional/semantic), and enabling AI via data products. Bonus: Background in data mesh designs and automated data access systems. Skilled in dev tools like Azure DevOps equivalents, Git-based version control, and orchestration platforms like Airflow. Strong organizational skills, precision, and adaptability in fast-paced settings with tight deadlines. Proven self-starter who thrives independently and collaboratively, with a commitment to ongoing tech upskilling. Bonus: Exposure to BI tools (e.g., Tableau, Power BI), though not central to the role. Familiarity with investment operations systems (e.g., order management or portfolio accounting platforms).