Staff Data Scientist - RiskOS

🇺🇸 Carson City, Nevada
Posted 3 days ago
Expires May 29, 2026
Full TimeRemote

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 THE ROLE

Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.

As a Staff Data Scientist for RiskOS, you will sit at the intersection of platform data science, fraud and risk analytics, and Generative AI. You will own end‑to‑end development of data‑driven solutions on the RiskOS platform—from heavy‑duty data exploration and cleaning, through modeling and GenAI agent design, all the way to production deployment and monitoring.

You will leverage your expertise in fraud and risk management to help develop and integrate robust detection and decisioning models, and your experience with Generative AI to design, evaluate, and operationalize LLM‑powered tools that improve analytics, workflows, and case investigations.

You will collaborate closely with engineering and platform teams to build scalable, production‑grade pipelines and services, and with product and risk leaders to ensure RiskOS delivers actionable insights, self‑serve analytics, and best‑in‑class fraud prevention at scale.

This is a highly collaborative, hands‑on technical leadership role for someone who enjoys owning complex data problems end‑to‑e...

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