Staff Machine Learning Scientist
- Location
- Remote (US)
- Job type
- Full-time
- Level
- Lead / Staff
- Experience
- 8+ years
- Education
- Bachelor's degree
- Listed
- 13 days ago
Skills & highlights for this role
- Production machine learning
- Consumer credit modeling
- Portfolio economics
- Risk-based decision systems
- Model validation
- Advanced Python
- Advanced SQL
- Statistical modeling
- Machine learning frameworks (PyTorch, XGBoost, or Spark)
- Experiment design
- Causal inference or holdout methodologies
- Technical leadership
- Stakeholder communication
Also useful
- Fintech or consumer lending experience
- Model risk management in regulated environments
- Fair-lending and adverse-action knowledge
- AI tools across the modeling lifecycle
About the role
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.
What Makes Someone Successful Here
- You connect technical decisions to business outcomes and member experiences. You bring strong scientific judgment, challenge assumptions thoughtfully, and build solutions that remain reliable as the business evolves.
- You collaborate across disciplines, welcome constructive feedback, and help others strengthen their work. When priorities change or challenges aren't fully defined, you create clarity and move forward with sound reasoning and shared accountability.
What to Expect
You'll have significant independence and influence across teams, supported by partners in Engineering, Product, Finance, Risk, and Compliance. Decisions are grounded in evidence, and you'll help shape the standards and processes that guide future work.
Ready to build for the underdog?
Don’t let imposter syndrome get in the way of an incredible opportunity. We’re looking for people who can help us achieve our mission and vision, not just check off the boxes. If you’re excited about this role, we encourage you to apply. You may just be the right candidate for this or other roles.
A few of our benefits & perks
- Opportunity to tackle tough challenges, learn and grow from fellow top talent, and help millions of people reach their personal financial goals
- Flexible hours and virtual-first work culture with a home office stipend
- Premium Medical, Dental, and Vision Insurance plans
- Generous paid parental and caregiver leave
- 401(k) savings plan with matching contributions
- Financial advisor and financial wellness support
- Flexible PTO and generous company holidays, including Juneteenth and Winter Break
- All-company in-person events once or twice a year and virtual events throughout to connect with your team members and leadership team
- #LI-REMOTE
Why Join Dave?
You'll tackle complex, meaningful challenges at the intersection of machine learning, financial access, and responsible innovation. You'll have the opportunity to shape company-wide technical practices while contributing directly to products that make a difference for millions of members.
Why you’ll love working here
At Dave, our people are just as important as our product. Our culture reflects the values that guide who we are, how we work, and what we aspire to be. Daves are member-centric, helpful, transparent, persistent, and better together. We strive to create an environment where all Daves feel valued, heard, and empowered to do their best work. As a virtual-first company, team members can live and work anywhere in the United States, except Hawaii.
Equal opportunity and legal notices
Dave Operating LLC is proud to be an Equal Employment Opportunity employer and is dedicated to cultivating a diverse and inclusive workplace. We will consider for employment all qualified applicants and do not discriminate on any basis protected by federal, state, or local law, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance relating to an applicant's criminal history.
From Dave's careers page, first listed on Rolev.ai on October 27, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
Where is the Staff Machine Learning Scientist job at Dave located?
Yes, this Staff Machine Learning Scientist opening at Dave is listed as Remote (US). Always check Dave's application page for specific state eligibility or relocation policies.
What qualifications are required for Staff Machine Learning Scientist at Dave?
For the Staff Machine Learning Scientist role, Dave highlights 8+ years of relevant experience; a bachelor's degree; experience with Production machine learning, Consumer credit modeling, Portfolio economics, Risk-based decision systems, Model validation, Advanced Python. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Staff Machine Learning Scientist position at Dave?
This listing links directly to Dave's Ashby application page. You can apply directly on Dave's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.