Data Scientist (RiskOS)

Description du poste

As a Data Scientist for Workforce Verification on the RiskOS team, you will own the end-to-end data science lifecycle for a critical new product area focused on workforce identity and hiring fraud You will explore and analyze rich, multi-source data (identity, device, behavioral, resume and application signals) to uncover fraud patterns in the hiring funnel, then translate those insights into rules, conditions, and machine learning models deployed within RiskOS workflows This role sits at the intersection of fraud analytics, natural language processing, and Generative AI You will help design and evaluate GenAI-powered components such as resume verification agents and explanation tools that operate on unstructured, text-heavy data like resumes, job descriptions, and interview artifacts The role is hands-on but not a “solo act”: you will be embedded in the RiskOS Data Science team, with guidance from senior data scientists and close partnership with product, engineering, and Workforce GTM It is ideal for a data scientist with strong fraud or risk experience who wants broader end-to-end ownership, enjoys working with unstructured text, and is comfortable rolling up their sleeves on data engineering and productionization when needed Own the full data science lifecycle for Workforce Verification use cases on RiskOS—from data exploration and hypothesis generation through model development, evaluation, deployment, and monitoring Explore and analyze workforce-related data sources (applications, resumes, device and behavioral telemetry, background checks, ATS/HRIS integrations) to identify patterns of workforce fraud such as fake resumes, identity rental, deepfake interviews, and injection attacks Design, implement, and iterate on rules, conditions, and heuristic logic in RiskOS workflows to detect high-risk workforce events (e.g., repeated identities across multiple resumes, suspicious device patterns, anomalous hiring flows) Develop and evaluate machine learning m

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