Head of Data Science, Compliance Products
Company websitesocure.com (Socure, opens in new tab)
Base salary $250K to $300K
Employer-published annual base salary, USD. Advertised base range in Hub, NY +3 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationHub, NY +3 more
- WorkplaceHybrid
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
All 4 locations
- Hub - San Francisco
- Hub - Miami
- Hub - New York
- Hub - Seattle
About this job
Why Socure?
Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
About Socure
Socure is building the identity trust infrastructure for the digital economy—verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity and compliance with a team that holds a high bar for itself, keep reading.
Role Overview
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).
You will lead teams delivering accurate, explainable, and production-ready models that help customers verify people, complete onboarding, screen against global watchlists, monitor risk, and meet evolving compliance needs. You will partner closely with Product, Engineering, Risk, Operations, and Go-to-Market leaders to turn complex customer and regulatory problems into measurable product outcomes. This role calls for a leader who combines strong technical judgment, team-building, and disciplined execution in high-stakes, data-rich environments.
Key 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.
Key Competencies & Qualifications
• 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 ML 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.
• Excellent communication skills, with the ability to explain complex systems and trade-offs to technical and non-technical audiences.
• Experience in customer-facing technical discussions, executive briefings, or public speaking is preferred.
Why Socure?
• Work on challenging, high-impact problems in identity verification and financial crime prevention.
• Build data science capabilities behind products used in important customer compliance workflows.
• Join a fast-moving, high-caliber team that values innovation, ownership, and customer impact.
• Competitive compensation, equity, and benefits.
• Help shape trusted digital experiences at global scale.
Please note that we can only hire within ~45 miles of San Francisco, New York, Seattle, Miami. We are unable to provide sponsorship support now or in the future.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process, including interview or onboarding support, please reach out to your Socure recruiting partner directly.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
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Source: Socure on Ashby · View original posting (opens in new tab)
Pay in context
This role's base floor ($250,000) is above 82% of the 1,731 Data & ML roles in California listed on this site; 23 others list the same floor. Their median floor is $184,000; the middle half runs from $154,300 to $224,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.
This listingHead of Data Science, Compliance Products$250K to $300K
Head of Data Science, Identity Graph$250K to $300K
Forward Deployed Engineer - RiskOS Agents$250K to $280K
Principal Product Operations Manager$247K to $297K
Staff Backend Engineer$225K to $265K
Staff Backend Graph Engineer$225K to $250K
AI Engineer$220K to $290K
Chart as a table
| Role | Published base |
|---|---|
| Head of Data Science, Compliance Products (this listing) | $250K - $300K |
| Head of Data Science, Identity Graph | $250K - $300K |
| Forward Deployed Engineer - RiskOS Agents | $250K - $280K |
| Principal Product Operations Manager | $247K - $297K |
| Staff Backend Engineer | $225K - $265K |
| Staff Backend Graph Engineer | $225K - $250K |
| AI Engineer | $220K - $290K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-11-06
Where this pay comes from
Location as the employer wrote it: Multiple locations (4)
USD 250,000 – 300,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
