The posting, in Chime's own words
archived Oct 8, 2026About the role
We're looking for a Sr. Product Data Scientist to partner with our Lending Product, Engineering, Risk, and Finance teams to drive measurable impact across Chime's portfolio of liquidity and credit products — MyPay, Instant Loans, SpotMe, and Line of Credit. You'll turn data into the decisions that shape how millions of members access liquidity, build credit, and get value from Chime — while balancing growth, member trust, and risk/compliance performance. This role sits at the intersection of product, data, experimentation, and risk. You'll own funnels end-to-end, design and analyze A/B tests, and translate ambiguous business questions into clear, prioritized recommendations that ship. You'll connect member liquidity outcomes to business metrics like revenue, losses, and Direct Deposit growth — not just product usage.
In this role, you can expect to
Operate as an independent thought partner to Lending Product, Engineering, Risk, and Finance — shaping strategy, not just measuring it. You'll proactively surface opportunities and risks, framing the right questions before they're asked. Build a rich experimentation and A/B testing program across MyPay, Instant Loans, and SpotMe — including metric creation, experiment design, power analysis, and results analysis. Drive data-informed decisions across the Lending org by equipping PMs and engineers with self-service analytics, and running ad hoc analyses and causal studies. Apply advanced causal inference, time-series, and forecasting methods to lending questions — origination pacing, adoption, repayment, and retention — plus occasional ML for member segmentation. Own metrics across the lending funnel — adoption, conversion, take rate, originations, revenue, retention, delinquency, losses, and Direct Deposit growth/retention — and use them to drive experiments. Help establish high-quality eventing to track member behaviors along liquidity and credit journeys through Chime's mobile app. Define what "good" looks like — optimizing for long-term member and business value while balancing growth against loss and risk — and build dashboards to track portfolio and product health. Translate complex findings into executive-ready narratives that inspire action and alignment.
Read the full posting ↓
To thrive in this role, you have
5–7 years of relevant hands-on experience in product or business data science (FinTech, lending, or credit a plus). Expert-level SQL ability and proficiency in Python. Broad knowledge of applied statistics, experimental design, and analysis of A/B tests. Demonstrated experience with techniques for applied business use cases. Demonstrated experience acting as a trusted advisor to senior cross-functional partners — influencing decisions through both data and judgment. Comfort speaking fluently in adoption, approval/conversion rates, and loss/risk tradeoffs is a strong plus. A strong bias toward proactive problem discovery. You don't wait for tickets — you explore data, spot patterns, and bring forward opportunities that meaningfully change product direction. Strong business intuition and judgment, and experience applying prioritization frameworks to your work (e.g., RICE, Eisenhower matrix). Exceptional data storytelling and ability. Experience with Hex and Looker a plus Familiarity with building data pipelines using tools like dbt or Airflow. Familiarity with AI coding tools (such as and Cursor). #LI-Hybrid #LI-AM1 Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $133,000 — $185,000 USD