Head of Data Science - Identity & Compliance

Socure Socure · Vertical AI · United States · Remote · Data Science & AI

Lead the Data Science function for Identity & Compliance, focusing on building and scaling AI-powered solutions including KYC, watchlist screening, and identity resolution. Drive the development of agent-driven systems for automated decisioning and investigation, leveraging graph neural networks and deep learning. Own the end-to-end model lifecycle and ensure alignment with regulatory requirements.

What you'd actually do

  1. 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.
  2. Lead, build, and develop a high-performing team of data scientists and applied researchers, fostering a culture of technical excellence, speed, and accountability.
  3. Architect and deploy advanced machine learning systems across identity verification, entity resolution, sanctions screening, and compliance risk modeling.
  4. 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.
  5. Lead the design and implementation of agent-based AI systems, enabling automated decisioning, case triage, investigation workflows, and adaptive compliance strategies.

Skills

Required

  • 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)
  • 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.

Nice to have

  • familiarity with graph ML frameworks
  • Experience representing organizations in customer-facing discussions, executive briefings, or public speaking engagements

What the JD emphasized

  • identity verification
  • KYC/AML
  • fraud detection
  • risk modeling
  • agentic system design
  • agent skills
  • orchestration/harness frameworks
  • real-world deployment of autonomous or human-in-the-loop agents
  • regulatory and compliance requirements

Other signals

  • AI-powered identity and compliance solutions
  • intelligent, agent-driven systems
  • graph-based intelligence
  • large-scale graph neural networks (GNNs)
  • agent-based AI systems
  • autonomous systems