Джерело: CrawlJobs
Ця вакансія не має повного перекладу вибраною мовою. Нижче показано оригінальний зміст.

Head of Data Science - Fraud Insights

Повна зайнятість Гібридна робота

Дата публікації: 31.08.2026

Socure sits on one of the most consequential datasets in the world — a global identity graph spanning hundreds of millions of identities, incorporating PII, device signals, behavioral telemetry, network relationships, and a continuous feedback loop of real-world fraud and verification outcomes across thousands of clients. We are looking for someone who can explain why it happened, predict what comes next, and make that story impossible to ignore — for regulators, customers, boards, and the market.

Responsibilities

Own the research agenda; Turn the identity graph into intelligence; Bridge the outside world to internal models; Tell stories that change minds; Build and lead a world-class team; Influence product, models and strategy; Represent Socure externally; Drive go-to-market differentiation

Requirements

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; Proven expertise in fraud, identity risk, financial crime, or adjacent domains; Strong command of causal inference, statistical modeling, and modern ML/AI techniques applied to adversarial or risk problems; Track record of external thought leadership — publications, conference presentations, regulatory engagement, or equivalent market-facing credibility; Exceptional written and verbal communication skills; Experience leading and developing high-performing technical teams; Research Depth & Econometric Rigor with panel data methods, diff-in-diff, regression discontinuity, survival analysis, network econometrics, and applied causal inference; Deep Fraud Domain Expertise in synthetic identity, first-party fraud, account takeover, bust-out rings, AML-adjacent typologies, mule networks, or related domains; Data Fluency at Scale with Python, SQL, graph analytics, and ML frameworks; External Credibility & Presence; Executive Communication Without Dumbing It Down; Regulatory & Macro-Intelligence Fluency with CFPB, FinCEN, state-level identity legislation, open banking frameworks

Nice to have

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
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