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Lead Machine Learning Scientist

Dave· Data & AI
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Remote$174k - $224kFull-timePosted 4d ago

About the role

Lead ML Scientist to develop and deploy advanced ML solutions for fraud detection and responsible credit expansion at Dave. Hands-on role across the full ML lifecycle with ownership of technically challenging problems and collaboration with Product, Engineering, and Risk Operations.

Responsibilities

  • Build and deploy advanced fraud detection models. Personally develop, train, validate, and optimize machine learning models that identify synthetic identities, first-party fraud, account takeover, and emerging fraud patterns.
  • Solve complex problems through data and experimentation. Explore large, diverse datasets, engineer predictive features, evaluate modeling approaches, and translate findings into production-ready fraud solutions.
  • Own the end-to-end ML lifecycle. Take models from initial research and prototyping through testing, deployment, monitoring, and continuous improvement, ensuring solutions deliver measurable business results.
  • Apply AI to accelerate machine learning development. Use modern AI tools and techniques to improve research, coding, feature development, experimentation, validation, and modeling workflows while maintaining strong technical rigor.
  • Optimize fraud decisioning through measurable results. Analyze model performance, fraud trends, approval rates, and portfolio outcomes to identify opportunities to improve detection accuracy, reduce losses, and support responsible growth.
  • Collaborate and contribute technical expertise. Partner with Engineering, Product, and Risk Operations to integrate models into production systems, solve implementation challenges, and share technical knowledge that strengthens the broader team.

Qualifications

  • 7+ years of hands-on machine learning experience, with a demonstrated track record of personally developing, deploying, and optimizing predictive models in production environments.
  • Deep fraud modeling expertise, including experience building ML solutions to detect identity fraud, synthetic identities, first-party fraud, and account takeover, ideally within fintech, consumer lending, or financial services.
  • Advanced proficiency in Python and SQL, with strong experience in feature engineering, model development, experimentation, performance evaluation, and production ML systems.
  • 4+ years of experience with ML frameworks and cloud technologies, including tools such as TensorFlow, PyTorch, Spark, and cloud-based ML infrastructure.
  • Experience leveraging generative AI and AI-assisted tools across research, coding, analysis, experimentation, testing, and model development, with sound judgment in validating outputs.
  • Strong analytical and business judgment, with the ability to evaluate trade-offs across fraud prevention, approval rates, profitability, compliance, and member experience.
  • Proven end-to-end execution, with the ability to independently tackle complex ML problems, make sound technical decisions, and deliver measurable results.
  • Strong communication and collaboration skills, including the ability to explain technical findings, partner across functions, and mentor fellow scientists through hands-on expertise.
  • Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, or equivalent practical experience.

Skills

Required:Machine learning model developmentFraud modelingPythonSQLML frameworks & cloud

Benefits

  • 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
Last updated Oct 22, 2026. Interested? Apply on the company site.
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