Senior Data Scientist (Lending)

• 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
• 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

Benefits

• Physical: We believe in taking care of your physical health, so as a Chimer you’ll get medical, dental, and vision insurance, as well as benefits to support your physical activity, family planning, and all of your little Chimers
• Emotional: We know that staying healthy involves a lot more than doctor’s checkups. We partner with Modern Health to help you navigate your mental health, give monthly Take Care of Yourself Days, and want you to take time off when you need it
• Financial: We want Chimers to save and feel financially supported, so we offer savings plans with competitive matching, as well as access to financial planning and legal assistance so that you can find your financial peace of mind
• Social: We’ll celebrate your milestones together with travel stipends, swag, and high-fives and make sure you’re connected to fellow Chimers through our Chime Resource Groups (CRGs) and company events- Familiarity with AI coding tools (such as Claude Code and Cursor)
• 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
• 5–7 years of relevant hands-on experience in product or business data science (FinTech, lending, or credit a plus)
• Exceptional data storytelling and data visualization ability. Experience with Hex and Looker a plus
• Expert-level SQL ability and proficiency in Python
• Strong business intuition and judgment, and experience applying prioritization frameworks to your work (e.g., RICE, Eisenhower matrix)
• Broad knowledge of applied statistics, experimental design, and analysis of A/B tests. Demonstrated experience with machine learning techniques for applied business use cases
• Familiarity with building data pipelines using tools like dbt or Airflow
• 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