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Socure is seeking a Director-level leader to build and scale the Data Science function across its identity and compliance product suite, including KYC, International KYC, Global Watchlist, Advanced Prefill, and Identity Graph. This role combines technical leadership with people management, requiring you to lead a high-performing team of data scientists and applied researchers while driving the technical vision for AI-powered identity verification and compliance solutions.
Key responsibilities include owning the data science strategy for identity and compliance products, delivering measurable improvements in accuracy, coverage, latency, and customer impact. You will architect and deploy advanced machine learning systems across identity verification, entity resolution, sanctions screening, and compliance risk modeling. A significant focus is developing graph-based intelligence, including large-scale graph neural networks (GNNs) and link analysis models to power Identity Graph and fraud detection. You will also lead the design and implementation of agent-based AI systems that enable automated decisioning, case triage, investigation workflows, and adaptive compliance strategies.
You will own the end-to-end model lifecycle—from data strategy and feature engineering through model development, evaluation, deployment, and monitoring. The role requires balancing model performance with explainability, auditability, and regulatory compliance. You'll partner closely with Product, Engineering, Risk, and Go-to-Market teams to translate business needs into scalable solutions. Additionally, you will serve as a trusted technical leader in customer engagements, clearly articulating model behavior, performance trade-offs, and roadmap decisions while representing Socure externally as a thought leader in identity, compliance, and applied AI.
Required qualifications include 10+ years of data science and machine learning experience with a proven track record of delivering production-grade AI systems at scale. You should have significant experience in identity verification, KYC/AML, fraud detection, or risk modeling in fintech or adjacent domains, plus demonstrated leadership experience managing and scaling high-performing data science teams. Deep expertise in modern ML techniques (deep learning, GNNs, entity resolution, large-scale data systems), agentic system design, and working with heterogeneous data sources (structured, text, network/graph, third-party signals) is essential. An advanced degree (MS/PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or related field is expected. Hands-on proficiency with Apache Spark, Python, and modern ML frameworks (PyTorch) is required; graph ML framework familiarity is a plus. Strong ability to engage with customers and stakeholders, explaining complex AI systems to both technical and non-technical audiences, is strongly preferred.
