Fraud Risk Analytics Manager
$105k - $130kCitizens Bank
Job Description 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
- 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
- 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
- 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
- Bachelor's degree in Operations Management, Mathematics, Statistics, Actuarial Sciences, Economics or other quantitative, business or technical discipline
- Master degree in Mathematics, Statistics, Operations Management, Economics or other quantitative, business or technical discipline preferred
- Hours per Week: 40
- Work Schedule: 8:00am-5:00pm Monday - Friday
Vacancy posted 7 hours ago
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