Senior Data Scientist, Lending

About 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. 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 machine learning 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…