Data Scientist, Senior Associate

We are seeking a Data Science Senior Associate focused on building and operating resilient datasets, pipelines, and reusable metrics that support hypothesis-driven analyses and experiments across the product development lifecycle (PDLC)

In this role, you will be hands-on in designing, developing, and maintaining data products that are reliable, observable, and well-documented-enabling partners across product, engineering, and analytics to measure what’s driving value, where friction exists, and how operating-model changes impact outcomes as teams adopt more agentic ways of working. You’ll contribute to engineering standards and help raise the quality bar through strong delivery and collaboration., * Build and operate scalable batch/streaming pipelines with SLAs, monitoring, and incident response participation (as needed).

• Create and maintain trusted data products (dimensions, event models, marts) with clear ownership and documentation.
• Deliver metrics and feature-ready datasets for AI adoption/productivity measurement; manage definition changes over time.
• Implement data quality and governance controls (validation, reconciliation, lineage, access, retention, auditability).
• Orchestrate workflows in Airflow (or equivalent), including backfills and retries.
• Model/transform data using SQL and dbt (or equivalent) for trusted reporting and repeatable measurement.
• Write production-grade Python/PySpark with testing, performance tuning, and maintainable design.
• Partner with cross-functional stakeholders to define requirements, success criteria, and metric interpretation across finance, PDLC/SDLC, and AI tool logs.
• Contribute to engineering best practices (version control, code review, CI/CD, runbooks) and improve observability and cost/performance.
• Mentor peers through reviews, documentation, and knowledge sharing (no formal people management).

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years building production data solutions; strong ownership and delivery.
• Strong engineering fundamentals (OOP, testing, development lifecycle).
• Strong data modeling skills (dimensional, normalized, event-based).
• Experience with Databricks and/or Spark/PySpark.
• Strong SQL; experience with dbt (or equivalent) and building testable data codebases.
• Experience operating orchestration pipelines (Airflow or equivalent).
• Proven ability to build and maintain reliable metrics as sources/definitions evolve.
• Effective delivery in ambiguous, multi-stakeholder environments.

Preferred Qualifications

• Experience with modern lakehouse/warehouse patterns and broader cloud data platforms (e.g., Databricks, Snowflake).
• Experience with BI/semantic layers and metrics management practices.
• Exposure to experimentation or hypothesis-driven analytics approaches (e.g., measurement design to support tests, rollouts, and pre/post evaluation); deep causal specialization not required.
• Experience improving observability (data freshness/SLA monitoring, lineage, alerting) and contributing to operational maturity (runbooks, incident follow-ups).

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, 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.

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs., Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.