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BILL · 3 days ago

Manager, Risk Data Scientist

San Jose, CA

Full-time

Hybrid

Senior Level

$167K/yr - $201K/yr

6+ years exp

BILL is a rapidly growing Fintech company focused on empowering businesses through innovative financial solutions. They are seeking a Manager to lead the Card Compromise Fraud Risk team, responsible for developing fraud detection strategies and managing data scientists to support BILL Card products.

AppsBillingFinancial ServicesFinTechSaaS

No H1B

Responsibilities

Lead Bill’s Card Compromise Fraud Risk team

Manage data scientists and collaborate with Cross Functional teams on key fraud risk initiatives

Take ownership of end-to-end strategy for real-time fraud detection and transaction risk monitoring

Design experiments to understand customer experience impacts when leveraging machine learning in risk strategy changes

Qualification

Fraud detection strategyData analysisStatistical modelingMachine learning techniquesRisk management methodologiesCard Compromise knowledgePayment Fraud domain knowledgeManagement experienceAnalytical abilitiesProblem solvingDecision makingOut-of-the-box thinking

Required

Minimum 6 years of total industry experience (incl. 2+ years in a people managerial position) in risk management within the Fintech or financial services industries with an emphasis on fraud risks

Bachelor's degree (advanced degree (M.S., PhD.) desirable), preferably in Statistics, Physical Sciences, Computer Science, Economics, Mathematics, or a related technical field

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

Extensive knowledge and experience with defining, developing, and deploying risk management methodologies

Strong track record of performing data analysis and statistical modeling using Python, SQL or similar tools

Machine learning techniques include clustering, classification, regression, decision trees, neural nets, anomaly detection etc

Ability to clearly communicate complex results to technical experts, business partners, and executives

Expertise in driving operational efficiencies and scale through ongoing policy and model optimization

Experience in managing and nurturing data scientists effectively

Experience working with cross functional teams including product, engineering and operations and leading organization-wide initiatives spanning multiple team

The ability to drive and influence cross functional teams on key projects, establish priorities while aligning with the business goals and vision

Strong analytical abilities. Familiarity with typical transaction data, systems & technologies is highly valuable