Note: The job is a remote job and is open to candidates in USA. BILL is a rapidly growing fintech company focused on financial automation to empower businesses. The Senior Manager, Risk Strategy Data Scientist will lead the development and operationalization of fraud and credit risk management strategies, leveraging data science and AI/ML tools to enhance fraud detection and risk mitigation. This role requires collaboration across multiple teams to drive risk strategy, policy optimization, and compliance for payment channels.
Responsibilities
- Building and maintaining the risk strategies and collaborate with cross functional teams to operationalize these risk strategies
- Formulate fraud and credit risk management strategies and controls for payments across different channels
- Use data to inform insights, influence stakeholders on relative priorities, management, refining risk strategies and driving initiatives
- Collaborate effectively with Product Management, Engineering teams to convey the strategy and work through the roadmap prioritization, planning and implementation
- Collaborate effectively with Customer success and sales teams while dealing with escalations and effectively communicating the risk policies to the broader organization
- Define, develop, and deploy risk management methodologies and models including data science and rule-based and predictive fraud models
- Drive operational efficiencies and scale through ongoing policy and model optimization
- Communicate and liaise effectively with the Compliance team and formulate the strategy for new product launches
- Manage cross-functional, multi-stakeholder processes, communicating and influencing stakeholders at various levels across functional boundaries
- Leverage AI/ML tools to strengthen fraud strategy, including using LLM-based signals, anomaly detection, or generative AI to identify emerging fraud patterns and inform rule and model development
- Use AI-assisted analytics platforms to accelerate fraud pattern recognition, risk scoring, and strategy iteration at scale
- Evaluate and govern AI-generated outputs within a fraud risk context, including assessing model drift, managing false positive/negative tradeoffs, and knowing when to override automated fraud decisions
Skills
- 8 years of experience in risk management within the Fintech or financial services industries with an emphasis on fraud and credit risks and 3 - 5 years in management
- Bachelor's degree
- Strong knowledge of the fundamentals of risk strategy such as fraud detection and prevention, balancing customer experience against rising fraud threats, using data to draw insights for risk mitigation
- Adept at SQL queries, reporting and presenting findings; Proficiency in Excel and other visualization tools
- Strong organization and time management skills and the ability to prioritize manage multiple projects at once
- Ability to collaborate effectively with Product Management, Engineering teams to convey the strategy and work through the roadmap prioritization, planning and implementation. Also collaborating effectively with Customer success and sales teams while dealing with escalations and effectively communicating the risk policies to the broader organization
- Extensive knowledge and experience with defining, developing, and deploying risk management methodologies and models including data science and rule-based and predictive fraud models
- Expertise in driving operational efficiencies and scale through ongoing policy and model optimization
- Communicate and liaise effectively with the Compliance team and formulate the strategy for new product launches
- Experience managing cross-functional, multi-stakeholder processes, communicating and influencing stakeholders at various levels across functional boundaries
- Strong analytical abilities. Familiarity with typical credit data, systems & technologies is highly valuable
- Hands-on experience leveraging AI/ML tools to strengthen fraud strategy, including using LLM-based signals, anomaly detection, or generative AI to identify emerging fraud patterns and inform rule and model development
- Demonstrated ability to evaluate and govern AI-generated outputs within a fraud risk context — including assessing model drift, managing false positive/negative tradeoffs, and knowing when to override automated fraud decisions
- MS/MA/MBA degree preferred in Business, Economics, Finance, Analytics, Mathematics, or a related field
- Familiarity with AI-assisted analytics platforms (e.g., Python-based ML libraries, AutoML tools, or vendor AI solutions) to accelerate fraud pattern recognition, risk scoring, and strategy iteration at scale
Benefits
- 100% paid employee health, dental, and vision plans (choose HMO, PPO, or HDHP)
- HSA & FSA accounts
- Life Insurance, Long & Short-term disability coverage
- Employee Assistance Program (EAP)
- 11+ Observed holidays and wellness days and flexible time off
- Employee Stock Purchase Program with employee discounts
- Wellness & Fitness initiatives
- Employee recognition and referral programs
Company Overview