About the Role
We are seeking a highly driven and innovative leader to build and scale the next generation of AI-powered identity and compliance solutions. This role will lead the Data Science function across core identity and compliance products, including KYC, International KYC, Global Watchlist, Advanced Prefill, and Identity Graph.
In addition to advancing core modeling capabilities, you will spearhead the development of intelligent, agent-driven systems that automate and optimize identity decisioning, investigation, and compliance workflows. You will define the technical vision and execution strategy for identity at scale, pushing the boundaries of machine learning, graph intelligence, and autonomous systems to solve some of the hardest problems in digital identity and regulatory compliance.
This role requires a leader who sets a high bar for execution, thrives in ambiguity, and consistently translates complex, high-stakes problems into scalable, production-grade systems.
What You'll Do
- Own and drive the data science vision for Identity & Compliance, delivering measurable improvements in accuracy, coverage, latency, and customer impact across all products in scope.
- Lead, build, and develop a high-performing team of data scientists and applied researchers, fostering a culture of technical excellence, speed, and accountability.
- Architect and deploy advanced machine learning systems across identity verification, entity resolution, sanctions screening, and compliance risk modeling.
- Drive the development of graph-based intelligence, including large-scale graph neural networks (GNNs) and link analysis models to power Identity Graph, fraud detection, and watchlist matching.
- Lead the design and implementation of agent-based AI systems, enabling automated decisioning, case triage, investigation workflows, and adaptive compliance strategies.
- Advance state-of-the-art modeling approaches, including deep learning, representation learning, graph learning, and multimodal fusion across structured and unstructured data.
- Drive innovation in Identity Graph and Prefill systems, improving identity resolution, linking, and enrichment capabilities across global datasets.
- Partner closely with Product, Engineering, Risk, and Go-to-Market teams to translate business needs into scalable AI solutions that deliver customer value.
- Own the end-to-end model lifecycle, including data strategy, feature engineering, model development, evaluation, deployment, and monitoring.
- Ensure alignment with regulatory and compliance requirements, balancing model performance with explainability, auditability, and governance.
- Continuously raise the bar on experimentation and execution velocity, enabling rapid iteration while maintaining high standards for reliability and impact.
- Own customer communication and stakeholder management, serving as a trusted technical leader in engagements with customers, partners, and internal stakeholders; clearly articulate model behavior, agentic systems, performance trade-offs, and roadmap decisions while building strong, long-term relationships.
- Represent Socure externally as a thought leader in identity, compliance, and applied AI.
What You Bring
- Advanced degree (MS/PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or a related field.
- 10+ years of experience in data science and machine learning, with a strong track record of delivering production-grade AI systems at scale.
- Significant experience in identity verification, KYC/AML, fraud detection, or risk modeling in fintech or adjacent domains.
- Proven leadership experience managing and scaling high-performing data science teams.
- Deep expertise in modern machine learning techniques, including deep learning, graph neural networks, entity resolution, and large-scale data systems.
- Strong understanding of agentic system design, including agent skills, orchestration/harness frameworks, and real-world deployment of autonomous or human-in-the-loop agents.
- Strong experience working with heterogeneous data sources, including structured data, text, network/graph data, and third-party identity signals.
- Demonstrated ability to drive ambiguous, high-impact problems to production, balancing speed, rigor, and business outcomes.
- Hands-on experience with Apache Spark and large-scale distributed data systems.
- Proficiency in Python and modern ML frameworks (e.g., PyTorch), and familiarity with graph ML frameworks is a plus.
- Proven ability to engage with customers and external stakeholders, clearly explaining complex AI systems, trade-offs, and outcomes to both technical and non-technical audiences.
- Experience representing organizations in customer-facing discussions, executive briefings, or public speaking engagements is strongly preferred.