Socure Head of Data Science, Compliance Products at Socure to lead data science vision and execution for AI-powered compliance products. Manage teams delivering models for KYC, AML, and global watchlist screening.
Responsibilities
We are seeking a highly driven, innovative data science leader to build and scale AI-powered compliance products. As Head of Data Science, Compliance Products, you will set the data science vision and lead execution across KYC, International KYC, Advanced Prefill, Deceased Check, Global Watchlist Screening and Monitoring, and Anti-Money Laundering (AML).
Define and own the data science strategy and roadmap for Compliance Products, aligning investments to customer outcomes, product priorities, and business goals.
Lead, grow, and develop a high-performing team of data scientists and applied researchers; set a high bar for technical quality, collaboration, speed, and accountability.
Advance machine learning and decisioning across KYC and International KYC, including identity verification, risk assessment, and onboarding workflows.
Improve Advanced Prefill through methods that select, validate, and rank relevant data to reduce customer effort while maintaining accuracy and transparency.
Develop and improve deceased-person detection and associated risk signals using reliable data, robust evaluation, and appropriate safeguards.
Build and scale Global Watchlist Screening and Monitoring capabilities, including entity matching, alert prioritization, ongoing monitoring, and false-positive reduction across geographies and data sources.
Advance AML and compliance risk models that help customers identify and investigate potentially suspicious activity, with clear performance measurement and appropriate human review.
Establish rigorous evaluation practices, including representative test data, segment-level performance, ongoing monitoring, drift detection, and feedback loops from customer and operations outcomes.
Own the end-to-end model lifecycle: data strategy, feature development, experimentation, validation, deployment, monitoring, and continuous improvement.
Ensure models and AI-enabled workflows are explainable, auditable, reliable, and designed to support applicable compliance and governance requirements.
Assess where automation and agent-assisted workflows can improve screening, monitoring, and investigations; define suitable human oversight and operational controls.
