S

Socure

Digital identity verification and fraud prevention

Head of Data Science - Compliance Products

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • An advanced degree (MS or PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • 10+ years of experience in data science and machine learning, including a strong record of delivering production systems at scale.
  • Significant experience in compliance, KYC/AML, watchlist screening, identity verification, fraud prevention, or risk modeling in financial services, fintech, or an adjacent domain.
  • Proven experience leading and developing high-performing data science teams.
  • Strong understanding of modern machine learning, statistical modeling, entity matching, information extraction, and decision systems.
  • Experience working with heterogeneous and large-scale data, including structured data, text, and third-party data sources.
  • Demonstrated ability to move ambiguous, high-impact problems from discovery to production while balancing rigor, speed, and business outcomes.
  • Hands-on experience with Python and modern machine learning frameworks such as PyTorch; experience with Apache Spark or comparable distributed data systems.
  • Practical understanding of model evaluation, monitoring, explainability, governance, and responsible deployment in regulated or high-stakes settings.
  • Ability to explain complex systems and trade-offs to technical and non-technical audiences.

Responsibilities

  • 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.
  • Partner with Product, Engineering, Risk, Operations, Legal/Compliance, and Go-to-Market teams to shape roadmaps and deliver scalable products.
  • Serve as a senior technical partner to customers and executives, explaining model behavior, performance, limitations, and trade-offs in clear terms.
  • Represent Socure externally as a thought leader in applied data science for identity verification and compliance.

Desired Qualifications

  • Experience in customer-facing technical discussions, executive briefings, or public speaking.

About the Company

Socure

Digital identity verification and fraud prevention

Socure provides digital identity verification and fraud prevention services for financial institutions through a subscription-based platform. It uses machine learning and advanced algorithms to analyze small amounts of customer data to predict fraud risk. A flagship feature, the Sigma Fraud Score, compares transactions against a proprietary database of known fraudulent users and traits to detect suspicious activity. Additional tools like Device Risk verify session authenticity by gathering device and browser signals, supporting seamless and secure customer experiences. Socure differentiates itself with a robust, data-driven fraud scoring system, a suite of identity verification and compliance tools, and continuous platform updates delivered as a service. Its goal is to help banks and other lenders verify customers quickly and accurately while reducing fraud and ensuring regulatory compliance (e.g., Customer Identification Programs under the Patriot Act).

Company size
501-1,000
Company stage
Series F
Total funding
$900.1M
Headquarters
Incline Village-Crystal Bay, Nevada
Founded
2012

Recently Posted Jobs

Explore more opportunities at Socure

See more jobs