Fraud Risk Analytics Manager

We are seeking an experienced **Senior Data Scientist** to lead fraud risk strategy optimization and entity‑level fraud state estimation across the enterprise. This role is critical to developing a **holistic understanding of customer behavior** and translating that understanding into **intelligent decisioning and colleague decision support** across fraud prevention, risk management, and product experiences. The ideal candidate brings deep fraud domain expertise spanning across the entire customer life cycle, strong analytical rigor, and the courage to challenge existing approaches while delivering practical, scalable solutions under time constraints and scope changes. This individual will partner closely with business leaders, first- and second-line risk teams, fraud operations, and product to drive measurable fraud risk reduction and improved customer outcomes. **Key Responsibilities** - Discover, Design, develop, and execute **fraud risk strategy optimization frameworks**, including rule, model, and hybrid decisioning approaches - Perform **entity‑level fraud state estimation** across customers, accounts, devices, and networks to enable consistent, enterprise‑wide fraud understanding - Translate complex fraud signals into **actionable insights and decision support** for colleagues across business, risk, and operations - Partner with first- and second-line risk teams to ensure strategies are **transparent, explainable, and well‑governed** - Collaborate with operations and product teams to ensure well-defined objective functions which are operationally viable and aligned with customer experience goals - Communicate findings clearly to both technical and non‑technical audiences, influencing decision‑making at multiple levels - Champion innovation by testing new analytical approaches while maintaining disciplined execution and production readiness **Required Qualifications** - **5+ years of experience** in fraud analytics, fraud risk management, or financial crime data science - Strong experience with **fraud detection, prevention, and decisioning systems** in complex environments - Demonstrated ability to balance **risk reduction, customer experience, and operational efficiency** - Proven track record of **independent problem‑solving**, ownership, and delivery in ambiguous problem spaces - Excellent communications (oral and written), interpersonal/business partnering, and organizational skills - Demonstrates **courage**, **innovation**, and **high productivity** - Bachelor's degree in Operations Management, Mathematics, Statistics, Actuarial Sciences, Economics or other quantitative, business or technical discipline **Technical Skills** - Advanced **SQL** for data extraction, transformation, and analysis - Strong **Python** skills for data analysis, modeling, and pipeline development - Solid foundation in **data science and statistical learning**, including: - Classification and regression techniques - Feature engineering - Model evaluation and performance monitoring **Preferred Qualifications** - Experience with **fraud strategy optimization**, challenger testing, or decision policy design - Familiarity with **entity resolution, graph/network analytics**, or customer‑centric risk frameworks - Experience operating within regulated environments and risk governance structures - Master degree in Mathematics, Statistics, Operations Management, Economics or other quantitative, business or technical discipline preferred **Hours & Work Schedule** - Hours per Week: 40 - Work Schedule: 8:00am-5:00pm Monday - Friday **Pay Transparency** The salary range for this position is $105,000 - $130,000 per year. Actual pay is based on various factors including but not limited to the **budget**, work location, and relevant skills and experience. We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and mor…