Dave vs. Goliath. We’re Dave.

Dave is a financial app on a mission to build products that level the financial playing field. It is redefining the financial landscape by leveraging technology to create an affordable, transparent, and user-centric access to liquidity for millions of Americans. As a leading innovator in the U.S. financial services sector, Dave’s digital financial platform offers products designed to meet the credit needs of those underserved by traditional financial institutions. Dave’s offerings include its flagship ExtraCash product, providing members up to $500 within minutes. The company is on track to launch several new product offerings in 2026, including a Buy Now Pay Later (BNPL) option.

Dave is focused on serving Americans who are financially vulnerable or living paycheck to paycheck. Dave is leading the charge in creating a new era of credit products that prioritizes speed, affordability, and accessibility, making it the go-to financial partner for those who need it most.

The Opportunity

We're looking for a Staff Machine Learning Scientist to shape how Dave builds, evaluates, and governs machine learning models across the business.

You'll set technical direction across credit, fraud, marketing, and growth while staying hands-on with high-impact modeling challenges. You'll establish practical governance standards, strengthen how we measure business outcomes, and help teams make better decisions with data. This role offers meaningful autonomy and the opportunity to influence how machine learning supports both our members and Dave's long-term growth.

What You'll Build and Own

Shape Dave's modeling strategy across underwriting, collections, fraud, marketing, and growth, influencing architecture, shared infrastructure, and investment priorities.

Establish model governance standards covering validation, monitoring, risk classification, documentation, change management, and independent review throughout the model lifecycle.

Build and improve credit models that inform underwriting, collections, and settlement strategies, balancing portfolio performance, profitability, and member outcomes.

Strengthen responsible modeling practices by partnering with Legal, Compliance, Risk, and sponsor-bank stakeholders to translate regulatory requirements into measurable controls.

Advance business measurement through meaningful metrics, experimentation, causal inference, and incrementality analysis that inform product and portfolio decisions.

Develop AI-assisted workflows and mentor scientists to improve modeling efficiency, evaluation quality, and consistency across teams.

The Impact

Your work will influence how Dave makes critical financial decisions, measures success, and manages risk. By building reliable models and scalable governance practices, you'll help us expand access to useful financial products while supporting responsible, sustainable growth.

What We're Looking For

8+ years of experience building production machine learning solutions, including demonstrated technical leadership at staff or principal scope.

Strong experience with consumer credit modeling, portfolio economics, and risk-based decision systems, ideally in fintech or consumer lending.

Experience with model validation, model risk management, or independent review in regulated environments, including familiarity with fair-lending and adverse-action considerations.

Advanced proficiency in Python, SQL, statistical modeling, and machine learning frameworks such as PyTorch, XGBoost, or Spark.

Experience designing experiments, defining business metrics, and measuring incremental impact through causal inference or holdout methodologies.

Demonstrated ability to influence technical direction and communicate complex trade-offs across senior stakeholders.

Practical experience using AI tools throughout the modeling lifecycle, with sound judgment in evaluating outputs.

A bachelor's, master's, or doctoral degree in a quantitative field, or equivalent experience.

Bonus: Experience evaluating or governing generative AI applications, including model guardrails and monitoring.