Staff Data Scientist, Fraud at Varo Money – San Francisco, California

Varo is the first consumer fintech with a national bank charter. We combine startup innovation with banking power to build financial inclusion for all.

Varo is looking for a Staff Data Scientist, Risk and Fraud, to serve as the technical cornerstone for fraud and risk prevention on our Data Science team. In this high-impact, individual contributor role, you will transition our fraud and risk operations from reactive "fire drills" to a state of engineering excellence. You will own the fraud/risk domain, acting as the primary technical liaison for cross-functional partners while instilling the rigorous testing and data science standards necessary for a world-class banking platform.

You aren’t just building models; you are architecting the future of trust at Varo. By providing senior technical leadership, you will streamline our modeling pipelines, mentor high-potential talent, and bridge the gap between complex data architecture and non-technical fraud experts. Your expertise will allow leadership to focus on strategy while you drive the execution and governance of our subprime lending and payment risk products. You will report to our Head of Data Science.

• Domain Ownership: Act as the primary technical lead for all fraud modeling and operations. Operate with full independence to resolve complex issues and lead technical communications.

• Engineering Rigor: Establish and implement robust testing protocols, model governance, and standard data science practices to ensure high-quality, compliant, and scalable outputs.

• Advanced Modeling: Design, develop, and maintain advanced fraud models tailored for banking and subprime lending. Utilize expert-level proficiency in predictive modeling, statistical analysis, and machine learning (e.g., XGBoost, Deep Learning) to detect fraud/risk.

• Strategic Cross-Functional Leadership: Serve as the primary technical partner for the Fraud/Risk Strategy, Operations, and Engineering teams. Ensure model outputs are accurate, operationally feasible, and seamlessly integrated into production.

• Mentorship & Cultural Impact: Provide technical guidance and debugging support to junior team members, fostering a culture of technical excellence and reducing operational bottlenecks.

• Model Monitoring & Governance: Establish and oversee monitoring frameworks to track model performance, feature drift, and data integrity in real-time. Define the "health" of our models to ensure they remain performant against evolving fraud vectors and meet strict Model Risk Management (MRM) standards.

• Deep Domain Expertise: Proven track record in financial industry fraud and/or risk modeling, ideally within subprime lending or high-volume payment environments.

• Technical Mastery: Advanced proficiency in Python, SQL, and the AWS stack, with a deep understanding of data architecture and MLOps.

• Strategic Communication: Exceptional ability to interface with non-technical stakeholders and regulatory bodies regarding model governance and compliance.

• Autonomous Execution: Demonstrated experience implementing technical rigor from the ground up, including automated testing, documentation, and lifecycle management.

• Modern Workflow: Proficiency with AI-assisted coding tools to accelerate development and manage a broad scope of technical responsibilities.

• Leadership Mindset: A track record of setting the bar for technical excellence, providing mentorship, and driving best practices for model validation and MRM compliance.

• Education: Master’s or PhD in a quantitative field (Statistics, Data Science, Economics, CS) or equivalent practical experience.

• Nice to have: Prior fintech experience and/or experience with 0-to-1 product development or startup environments a plus.

Varo is an equal opportunity employer. Varo embraces diversity and we are committed to building teams that represent a variety of backgrounds, perspectives, and skills. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

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