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# Machine Learning Scientist

- **Company:** Dave, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $150,000.0 - $187,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Python (Programming Language), Machine Learning, SQL Databases, Information Technology, Data Analytics, Performance Monitor
- **Published:** September 20, 2026
- **Apply:** https://www.builtincolorado.com/job/senior-machine-learning-scientist/11286901?handler=ApplyRedirect

## About the Role

* 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 the ability to explain complex technical and credit decisions to senior and cross-functional stakeholders.
 * Bachelor's or master's degree in a quantitative discipline such as computer science, mathematics, statistics, economics, or engineering.

Bonus: PhD in a quantitative discipline.

## Description

* Develop and optimize underwriting, settlement, and collection strategies across ExtraCash, FlexCard, and Rent, translating risk appetite into policies, decision rules, exposure strategies, and portfolio guardrails.
 * Build ML- and AI-enabled credit strategies using cash-flow, income, behavioral, bureau, and alternative data, with ownership of methodology, validation, and production recommendations.
 * Design rigorous experimentation and evaluation frameworks, including success metrics, scenario analyses, guardrails, and launch recommendations.
 * Partner with Product, Engineering, ML Platform, Finance, Legal, and Compliance to develop scalable decisioning solutions and improve strategies throughout the credit lifecycle.
 * 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.

The Impact

Your work will directly influence how Dave expands responsible access to financial products while maintaining sustainable credit performance. The decisions you help shape will affect member experience, portfolio economics, and Dave's ability to build differentiated products at scale., You take responsibility for outcomes, not just models or analyses. You connect technical decisions to member experience and business performance, make thoughtful trade-offs, and build approaches that hold up over time. When the path isn't fully defined, you use data and judgment to help shape it.

You also work well across disciplines. You invite feedback, communicate your reasoning clearly, and help other scientists strengthen their work. As new information changes the problem, you adjust without losing sight of the broader goal.

What to Expect

You'll have meaningful autonomy and a high degree of ownership. Decisions are data-driven, priorities will evolve as we learn, and you'll work closely with partners across Dave to turn analysis into durable production solutions.

Why Join Dave

You'll help shape credit decisions across multiple growing products, work with differentiated alternative data, and influence both technical systems and business strategy. You'll have room to build new approaches, improve how the team works, and contribute directly to products designed for members who are often underserved by traditional financial institutions.