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Dave

Fee-free mobile banking with cash advances

Lead Machine Learning Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA$174k - $224k /yr

About the Job

Requirements

  • At least 7 years of hands-on machine learning experience, including personally developing, deploying, and optimizing predictive models in production environments.
  • Deep fraud-modeling expertise, including machine-learning solutions for identity fraud, synthetic identities, first-party fraud, and account takeover.
  • Advanced proficiency in Python and SQL, with experience in feature engineering, model development, experimentation, performance evaluation, and production machine-learning systems.
  • At least 4 years of experience with machine-learning frameworks and cloud technologies, including tools such as TensorFlow, PyTorch, Spark, and cloud-based machine-learning infrastructure.
  • Experience leveraging generative artificial intelligence and AI-assisted tools in research, coding, analysis, experimentation, testing, and model development, and sound judgment in validating outputs.
  • Ability to evaluate trade-offs across fraud prevention, approval rates, profitability, compliance, and member experience.
  • Ability to independently tackle complex machine-learning problems, make sound technical decisions, and deliver measurable results.
  • Ability to explain technical findings and collaborate across functions; ability to 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.

Responsibilities

  • Personally develop, train, validate, and optimize machine-learning models that identify synthetic identities, first-party fraud, account takeover, and emerging fraud patterns.
  • Explore large, diverse datasets, engineer predictive features, evaluate modeling approaches, and translate findings into production-ready fraud solutions.
  • Own the end-to-end machine-learning lifecycle, from initial research and prototyping through testing, deployment, monitoring, and continuous improvement, ensuring solutions deliver measurable business results.
  • Use modern AI tools and techniques to improve research, coding, feature development, experimentation, validation, and modeling workflows while maintaining technical rigor.
  • Analyze model performance, fraud trends, approval rates, and portfolio outcomes to identify opportunities to improve detection accuracy, reduce losses, and support responsible growth.
  • 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.

Desired Qualifications

  • Experience in fintech, consumer lending, or financial services is ideal.
  • Experience with graph databases, graph-based fraud detection, or network analytics.

About the Company

Dave

Fee-free mobile banking with cash advances

Dave is a fintech app that provides free or low-cost banking features to help people manage money more easily. Its mobile app offers cash advances on upcoming paychecks with no interest or credit checks, a debit card backed by a partner bank, and services like Side Hustle and LevelCredit to boost income and credit. Unlike many peers, Dave focuses on fee-free basics for lower- and middle-income users, avoiding overdraft, minimum balance, and ATM fees, while charging for optional subscriptions and add-ons. Its goal is to help users avoid common banking costs and improve financial stability through simple, accessible tools.

Company size
501-1,000
Company stage
IPO
Headquarters
Los Angeles, CA
Founded
2016

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