# Head of Data Science - Core Insights at Socure

- Company: Socure
- What the company does: Socure is the leading AI-powered identity verification platform trusted by 3,000+ customers to verify consumers, businesses, & employees with confidence. Backed by Accel.
- Company website: https://www.socure.com/
- Type: Startups
- Level: Principal and up
- Location: Hybrid - San Francisco, CA
- Work setup: Remote
- Pay: $250K to $300K base salary per year (USD)
- Posted: 2026-07-27
- Apply by: 2026-10-12
- Apply: https://jobs.ashbyhq.com/socure/82e9f9f6-3896-42d1-b91b-d9ecaa36c6a8
- Page: https://www.1752.vc/careers/jobs/socure-head-of-data-science-core-insights/

## About the role

Socure sits on one of the most consequential datasets in the world — a global identity graph spanning hundreds of millions of identities, incorporating PII, device signals, behavioral telemetry, network relationships, selfie and document images, and a continuous feedback loop of real-world fraud and verification outcomes across thousands of clients. The patterns inside this graph tell the story of how fraud evolves: who the adversaries are, how they adapt, and where they're going next.

## What they're looking for

- Executive Communication Without Dumbing It Down. You can write a 2-page brief for a CEO that captures all the important nuances, and go 10 levels deep with a PhD data scientist without losing them
- Regulatory & Macro-Intelligence Fluency. You follow the regulatory environment — CFPB rulemaking, FinCEN guidance, state-level identity legislation, open banking frameworks — and understand how policy changes alter fraud incentives and attack surfaces
- Advanced degree (MS or PhD strongly preferred) in Data Science, Computer Science, Statistics, Applied Mathematics or a related quantitative field
- 10+ years of applied experience in data science, fraud analytics, risk research, or quantitative economics, with demonstrable impact at scale
- Proven expertise in fraud, identity risk, financial crime, or adjacent domains
- Strong command of causal inference, statistical modeling, and modern ML/AI techniques applied to adversarial or risk problems

Tags: AI and Data