Head of Data Science (Fraud Insights)

Join Socure, a leading provider of digital identity verification and fraud prevention solutions. As the Head of Data Science (Fraud Insights), you will be at the forefront of understanding and combating fraud. You will own the research agenda, turn the identity graph into intelligence, bridge the outside world to internal models, tell compelling stories, build and lead a world-class team, influence product and strategy, represent Socure externally, and drive go-to-market differentiation. This is a remote position with a comprehensive benefits package.

• Own the Research Agenda by designing studies and analytical frameworks that produce findings you can stand behind publicly.
• Work across Socure's global identity graph to surface fraud rings, adversarial coalitions, emerging attack typologies, and behavioral shifts.
• Serve as the connective tissue between external signals and Socure's internal research, modeling, and product roadmaps.
• External Credibility & Presence. You have a track record of representing an organization publicly and credibly — major conference appearances, regulatory working groups, authored research the market takes seriously, or a reputation that precedes you in the fraud and identity space
• Research Depth & Econometric Rigor. You approach fraud data the way a serious economist approaches a policy question — with proper identification strategies, an appreciation for confounding, a healthy skepticism of naive correlations, and the discipline to distinguish causation from coincidence. Comfortable with panel data methods, diff-in-diff, regression discontinuity, survival analysis, network econometrics, and the full toolkit of applied causal inference
• Regulatory & Macro-Intelligence Fluency. You follow the regulatory environment — CFPB rulemaking, FinCEN guidance, state-level identity legislation, open banking frameworks — and understand how policy changes alter fraud incentives and attack surfaces
• Executive Communication Without Dumbing It Down. You can write a 2-page brief for a CEO that captures all the important nuance, and go 10 levels deep with a PhD data scientist without losing them. You know the difference between simplifying and falsifying, and you never do the latter
• Data Fluency at Scale. You've worked with large-scale identity, behavioral, or transaction datasets. You understand graph structures, feature engineering at the identity level, and the operational realities of productionizing insights. Conversant in Python, SQL, graph analytics, and ML frameworks
• Deep Fraud Domain Expertise. You've spent meaningful time in the trenches — synthetic identity, first-party fraud, account takeover, bust-out rings, AML-adjacent typologies, mule networks, or related domains. You understand the adversarial game theory at play and respect the sophistication of the actors on the other side
• Proven expertise in fraud, identity risk, financial crime, or adjacent domains
• Exceptional written and verbal communication skills; ability to author compelling, rigorous, market-facing research
• Experience leading and developing high-performing technical teams
• Track record of external thought leadership — publications, conference presentations, regulatory engagement, or equivalent market-facing credibility
• Advanced degree (MS or PhD strongly preferred) in Economics, Statistics, Econometrics, Applied Mathematics, Computer Science, or a related quantitative field
• 10+ years of applied experience in data science, fraud analytics, risk research, or quantitative economics, with demonstrable impact at scale
• Strong command of causal inference, statistical modeling, and modern ML/AI techniques applied to adversarial or risk problems
• Experience with graph-based analytics, identity network modeling, or fraud ring detection using Neo4j, AWS Neptune, or custom graph frameworks
• Familiarity with the regulatory landscape governing identity verification, fraud prevention, and consumer financial protection (CFPB, FinCEN, OCC, state AGs)
• Experience with device intelligence, behavioral biometrics, email/phone/IP signals, or browser fingerprinting in a fraud context
• Published research or white papers in peer-reviewed journals, industry publications, or prominent market forums
• Experience working in or alongside financial services, fintech, credit bureaus, payments networks, or fraud consortia
• Exposure to explainable AI, model governance, or adverse action frameworks relevant to consumer-facing decisioning