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About the Role Chime is the largest and fastest-growing U.S. player in the challenger-banking space. Through our banking partners, we offer access to bank accounts with fee-free overdraft, provide members the chance to receive early access to their paychecks, help them improve their credit, and more. We created Chime because we believe everyone deserves financial peace of mind. We’re looking for a Lead Data Analyst to drive forecasting for key growth and revenue drivers and deliver insights that shape business decisions. You’ll own end-to-end forecasting workstreams such as member growth, purc
Key Responsibilities
- 1Own core forecasting workstreams for key business metrics (e.g., member growth, purchase volume, deposit volume), including in-year outlooks and contributions to longer-range forecasting.
- 2Build, maintain, and improve forecasting models that are accurate, transparent, and scalable; document assumptions and create repeatable processes.
- 3Run intramonth pacing, variance, and sensitivity analyses, identifying key drivers and surfacing risks/opportunities early.
- 4Develop scenarios and “what-if” analyses to support planning and real-time decision-making (e.g., upside/downside cases, impact of product or marketing changes).
- 5Partner cross-functionally to align inputs and assumptions, reconcile differences across reporting/forecasting views, and ensure a single source of truth where possible.
- 6Own unit economics and profitability analytics, including LTV/CAC, ROI analysis, and framework development for evaluating product and growth initiatives.
- 7Improve dashboards and forecasting tooling (spreadsheets, Looker/Pigment or similar) to increase visibility, consistency, and speed of insight.
Requirements
- 4–8 years of experience in forecasting, finance analytics, strategic finance, or a similar quantitative role (fintech/payments/consumer financial services is a plus).
- Demonstrated ability to own forecasting end-to-end and deliver decision-driving insights to senior stakeholders.
- Strong modeling instincts: comfortable living in the details (assumptions, drivers, sensitivities) while keeping the business story straight.
- Excellent communication: able to translate analytical output into crisp narratives, tradeoffs, and recommendations for technical and non-technical audiences.
- Expert SQL skills - able to translate business questions into robust queries, understand edge cases, and explore a warehouse efficiently to find the right data.
- Proficiency in Python or R - writes reproducible, well-structured code with a tendency toward automation and scalable analysis.
- High accountability, strong judgment, and comfort operating in ambiguity and fast-moving environments.
Perks & Benefits
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