Lead Machine Learning Scientist
About The Position
Dave is seeking a hands-on Lead Machine Learning Scientist to develop and deploy advanced machine learning solutions for fraud detection, member protection, and responsible access to credit. The role spans the full machine learning lifecycle, from exploring large datasets and developing predictive models to production deployment, performance evaluation, monitoring, and ongoing improvement. The scientist will own technically challenging problems and influence fraud detection and risk decisioning while collaborating with Product, Engineering, and Risk Operations. The role focuses on identifying synthetic identities, first-party fraud, account takeover, and emerging fraud patterns. It also involves applying AI-assisted methods to accelerate research and model development, and evaluating fraud trends, approval rates, and portfolio outcomes to improve detection accuracy, reduce losses, and support responsible growth. The work is intended to reduce fraud losses, improve decision accuracy, and help more members access financial tools. The position offers autonomy in a collaborative, virtual-first company that values technical excellence, meaningful ownership, and sustainable performance. Team members can live and work anywhere in the United States except Hawaii.
Requirements
- 7+ years of hands-on machine learning experience, with a track record of 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.
- Strong experience in feature engineering, model development, experimentation, performance evaluation, and production machine learning systems.
- 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 using generative AI and AI-assisted tools for research, coding, analysis, experimentation, testing, and model development, with sound judgment in validating outputs.
- Strong analytical and business judgment, including evaluating trade-offs among 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.
- Strong communication and collaboration skills, including explaining technical findings and partnering across functions.
- Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, or equivalent practical experience.
Nice To Haves
- Experience in fintech, consumer lending, or financial services.
- Experience with graph databases, graph-based fraud detection, or network analytics.
Responsibilities
- Personally develop, train, validate, and optimize machine learning models to detect synthetic identities, first-party fraud, account takeover, and emerging fraud patterns.
- Explore large, diverse datasets, engineer predictive features, evaluate modeling approaches, and turn findings into production-ready fraud solutions.
- Own models through research, prototyping, testing, deployment, monitoring, and continuous improvement.
- 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 improve detection accuracy, reduce losses, and support responsible growth.
- Collaborate with Engineering, Product, and Risk Operations to integrate models into production systems and address implementation challenges.
- Share technical knowledge and mentor fellow scientists through hands-on expertise.
- Communicate technical findings and contribute to cross-functional product and business decisions.
Benefits
- Home office stipend.
- Premium medical, dental, and vision insurance plans.
- Paid parental and caregiver leave.
- 401(k) savings plan with matching contributions.
- Financial advisor and financial wellness support.
- Flexible PTO and company holidays, including Juneteenth and Winter Break.
- All-company in-person events once or twice a year and virtual events throughout the year.
- Flexible hours and a virtual-first work culture.
- Opportunities to learn and grow from fellow top talent.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
