Define the product and data strategy for the Data Risk Hub, including the roadmap, use cases, and commercialization approach for fraud and risk intelligence offerings, with a strong focus on the strategic advantage arising from comprehensive data.
Identify and prioritize high-value fraud, identity, payments, and behavioral risk signals across merchant acquiring, issuing, banking, and cross-ecosystem data sources.
Partner with IT, engineering, and data science teams to design, build, and activate scalable risk signals, decisioning inputs, scores, application programming interfaces (APIs), and insight products.
Translate complex fraud, data, and analytics concepts into clear business value propositions that support product strategy, client adoption, and revenue growth where data is the key component and technology is the delivery layer.
Collaborate with product, sales, legal, compliance, and other cross-functional teams to bring fraud intelligence capabilities to market in a way that aligns with business objectives and regulatory requirements.
Evaluate market opportunities, client needs, and competitive offerings to shape differentiated fraud intelligence solutions that leverage Fiserv data advantages.
Measure product performance through adoption, signal quality, revenue contribution, and client impact, and refine strategy based on measurable outcomes.

12+ years of experience in fraud, risk, payments, data science, or financial services analytics.
Experience in technology, data science and fraud operations building fraud models, risk platforms, data products, or decisioning capabilities.
Understanding of payments, card fraud, merchant risk, banking fraud, and identity risk.
Executive presence and experience turning complex technical ideas into business value.
Bachelor’s Degree in data science, computer science, engineering, mathematics, statistics, finance, or a related field, or equivalent combination of education, related experience and/or military experience.
Experience with fraud and identity platforms, network intelligence, entity resolution, graph analytics, or machine learning model deployment (preferred).
Experience commercializing data products in payments, fintech, banking, or fraud technology environments (preferred).
Experience presenting product strategy, data concepts, and business cases to executive leaders, clients, or external partners (preferred).

Incentive eligible associates may receive an annual incentive opportunity which may be delivered as a mix of cash bonus and equity awards

Senior Director, Fraud Data, Signals and Risk Intelligence

Key skills