Fraud Strategy Data Scientist

About the role

Join BILL’s Fraud Risk Strategy team and lead key projects in fraud detection, risk analysis, and loss mitigation. This role focuses on refining risk strategies, developing predictive algorithms, and driving data-driven decision-making to combat financial fraud in a rapidly growing fintech environment.

Responsibilities

• Design, create, and execute control strategies to achieve ambitious business goals, including complex analytical rule development and maintenance.
• Develop, maintain, and refine risk strategy frameworks to ensure high performance and alignment with KPIs.
• Build and deploy data-driven, automated monitoring rules to detect and respond to evolving risk trends.
• Partner with product and engineering teams to capture risk signals and implement treatments across customer touchpoints.
• Utilize advanced analytics (SQL, Python) to solve ambiguous problems and refine end-to-end control strategies.
• Interpret results and use data findings to influence decision-making across the organization.
• Create flexible performance dashboards and monitoring tools (e.g., Tableau) to share actionable insights with stakeholders.
• Apply expertise in financial fraud risk data, metrics, and typologies to enhance existing strategies and processes.
• Identify and recommend enhancements, such as data feature improvements, enrichment, and score recalibration.
• Lead new model, rule, or product opportunities to optimize processes and align with business goals.
• Collaborate with cross-functional teams (modeling, product, engineering, operations) to design strategies across the customer lifecycle.
• Establish business requirements, shared KPIs, guide execution, and perform validation and maintenance.
• Mentor junior team members and support their professional growth.
• Apply AI to accelerate data science work, including prompt design, output evaluation, and LLM integration via APIs.
• Design experiments, analyze fraud typologies (e.g., onboarding fraud/abuse), and ensure data/control governance through proposal development, validation, and approval workflows.

Requirements

• Minimum 3+ years of end-to-end fraud risk control strategy experience in eCommerce, online payments, or a related industry.
• Proven track record of achieving business goals through analytical rule development and cross-functional collaboration.
• Hands-on experience with complex data wrangling, diagnostic analytics, and storytelling using tools like Tableau.
• Advanced knowledge of data, metrics, and key indicators in the financial fraud risk domain.
• Experience influencing cross-functional team approaches and project leadership.
• Proficiency in building complex SQL/Python scripts with minimal guidance to solve ambiguous problems.
• Experience applying AI to data science work, including prompt design and LLM integration.
• Familiarity with experimental design, fraud typologies, and data/control governance workflows.

Pay

Estimated salary ranges for this role vary by geographic zone:

• Zone 1: San Francisco Bay Area, New York City, Seattle, Los Angeles County: $112,700–$135,000 USD
• Zone 2: Non-Bay Area/LA California, Austin, Massachusetts: $101,400–$121,500 USD
• Zone 3: Utah, Dallas, Houston, Florida, North Carolina, Illinois, Colorado, Arizona, Georgia, Oregon, Pennsylvania: $95,800–$114,800 USD

Benefits

• 100% paid employee health, dental, and vision plans (HMO, PPO, or HDHP options).
• HSA & FSA accounts.
• Life insurance, long- and short-term disability coverage.
• Employee Assistance Program (EAP).
• 11+ observed holidays, wellness days, and flexible paid time off.
• Employee Stock Purchase Program with discounts.
• Wellness and fitness initiatives.
• Employee recognition and referral programs.

Visa sponsorship is not available for this position. Applicants must have authorization to work in the United States without requiring sponsorship now or in the future.