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# Actuarial Data Scientist at Shepherd

- **Company:** Jack & Jill, Inc.
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Python (Programming Language), Project Management Software, SQL Databases, Real Time Data, Autodesk Autocad
- **Published:** July 16, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p51q8suel0

## About the Role

* 3+ years of professional experience building and deploying predictive pricing models for personal or commercial auto insurance in production environments.
 * Strong command of statistical methods including GLMs, GBDTs, and Bayesian methods, alongside proficiency in Python and SQL.
 * An AI-native mindset with the ability to reason from first principles and communicate complex findings to non-technical stakeholders.

## Description

You will join the Actuarial & Predictive Analytics team to own end-to-end commercial auto pricing models. By building and deploying sophisticated loss cost models and feature pipelines, you'll directly influence Shepherd's underwriting quality and market expansion. This high-impact role blends statistical rigor with shipping real products to achieve the industry's first fully autonomous underwriting., * Work at the cutting edge of insurtech, building the industry's first fully agentic submission system for complex commercial construction projects.

 * Benefit from strong backing and industry validation, following a $42M Series B led by Intact Private Capital, one of the world's largest insurers.
 * Directly shape the risk infrastructure for the next generation of financial services, leveraging real-time data from partners like Procore and Autodesk.

What You Will Do

 * Own commercial auto pricing models end-to-end, from initial feature development through production deployment and iterative refinement.
 * Design and maintain robust feature pipelines that transform raw submission, claims, and third-party data into high-quality model inputs.
 * Collaborate closely with actuaries and underwriters to translate domain expertise into predictive features that improve pricing accuracy and loss ratios.


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