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Dave is a fintech company building financial products for underserved Americans, offering affordable access to liquidity through products like ExtraCash (up to $500 loans), FlexCard, and Rent. The company uses alternative data—cash-flow, income, behavioral, bureau data—to make credit decisions differently than traditional lenders.
You will serve as Senior Machine Learning Scientist, working at the intersection of consumer credit, machine learning, AI, analytics, and product strategy. This is a new role reporting to the Sr. Manager of Underwriting and Credit Science, giving you meaningful autonomy and ownership over credit science across multiple products.
Key responsibilities:
- Develop and optimize underwriting, settlement, and collection strategies across ExtraCash, FlexCard, and Rent, translating risk appetite into policies, decision rules, and portfolio guardrails.
- Build ML- and AI-enabled credit strategies using alternative and traditional data, with full ownership of methodology, validation, and production recommendations.
- Design rigorous experimentation and evaluation frameworks, including success metrics, scenario analyses, and launch recommendations.
- Partner with Product, Engineering, ML Platform, Finance, Legal, and Compliance to develop scalable decisioning solutions.
- Monitor portfolio and business performance, identify emerging opportunities or risks, and translate analysis into clear recommendations.
- Build reusable modeling, analytics, and AI-assisted workflows that improve development, testing, validation, documentation, and monitoring.
You will directly influence how Dave expands responsible access to financial products while maintaining sustainable credit performance. Your work affects member experience, portfolio economics, and Dave's ability to build differentiated products at scale.
The role emphasizes taking responsibility for outcomes, not just models. You connect technical decisions to member experience and business performance, make thoughtful trade-offs, and build approaches that hold up over time. You work well across disciplines, invite feedback, communicate clearly, and adjust as new information emerges.
Dave is virtual-first; team members can live and work anywhere in the United States (except Hawaii). Benefits include flexible hours, home office stipend, premium medical/dental/vision, generous paid parental leave, 401(k) matching, financial wellness support, flexible PTO, and all-company in-person events.
REQUIREMENTS:
- 5+ years of experience in consumer credit risk, underwriting, settlement and collection, machine learning, or predictive analytics, ideally in fintech or consumer lending.
- Strong hands-on experience with statistical modeling, machine learning, experimentation, and production decision systems.
- Proficiency in Python and SQL.
- Experience developing credit strategies across the product lifecycle, from new-product launches through mature portfolios.
- Deep understanding of credit policy, risk appetite, portfolio management, credit performance monitoring, and settlement and collection.
- Experience working with cash-flow, income, behavioral, bureau, or other alternative data.
- Experience using AI-assisted tools across research, coding, analysis, model development, testing, or documentation while maintaining strong judgment over output quality.
- Strong communication skills and ability to explain complex technical and credit decisions to senior and cross-functional stakeholders.
- Bachelor's or master's degree in a quantitative discipline (computer science, mathematics, statistics, economics, or engineering).
- Bonus: PhD in a quantitative discipline.
