Actuarial Data Science Lead

About this role

WHAT WE DO

Yesterday's insurance wasn't built for today's risk. We see it in the data and we feel it in the field. Emerging technology can reinvent how risk is priced and managed, faster and smarter, anchored in proven expertise. First-movers will define the next era of commercial risk management, and Shepherd is building it.

Shepherd is a technology-driven Managing General Underwriter (MGU) transforming commercial Property & Casualty insurance for high-hazard industries. Our mission is to make risk frictionless for the builders and operators shaping the physical world, protecting progress from concept through construction and into decades of operation.

We're building the fastest, smartest commercial risk platform, where underwriting expertise, data, and automation work together to deliver:

- Faster decisions

- Smarter, more accurate pricing

- Better risk outcomes

With Shepherd, safety, speed, and quality no longer trade off against one another. They compound. We're not just modernizing insurance products. We're building the risk infrastructure for the next generation of financial services, where technology, underwriting, and partnerships operate in harmony to support the world's most important industries and the progress they make possible.

OUR INVESTORS

In March 2026, Shepherd raised a $42M Series B https://www.linkedin.com/posts/justindlevine29_today-were-announcing-our-42m-series-b-activity-7442200922291630080-z1gw?rcm=ACoAAAkOMEwBRnAAXmdnQcaOJeioCu6VCqR6Gzc&utm_medium=member_desktop&utm_source=share — bringing total funding to over $60M — led by Intact Private Capital, the investment arm of one of the largest insurers in the world. Intact is not only our lead investor but also a carrier partner, a testament to the confidence the incumbent industry has in what we're building. Our investors:

- Intact Private Capital https://www.intactfc.com/about-us/intact-ventures, led our Series B round

- Costanoa Ventures https://costanoa.vc/, led our Series A round

- Spark Capital https://www.sparkcapital.com/, led our Seed round

- Susa Ventures https://www.susaventures.com/, lead our Pre-Seed round

- Y Combinator https://www.ycombinator.com/

- And several others

OUR TEAM

We're a team of technologists and insurance enthusiasts, bridging the two worlds together. Check out our About https://www.shepherdinsurance.com/about page to learn more.

ABOUT THE ROLE

Shepherd is building the data infrastructure and predictive models that power modern commercial insurance. As an Actuarial Data Science Lead on the Actuarial & Predictive Analytics team, you will own the development of pricing models starting with commercial auto, one of our highest-volume and most data-rich lines. You'll directly shape the quality of the book we write and the products we bring to market.

This is a high-impact, individual-contributor role for someone who thrives at the intersection of statistical rigor and shipping real products. You will work closely with actuaries, underwriters, and engineers to turn data into decisions.

WHAT YOU'LL DO

- Own commercial auto pricing models end-to-end from feature development through deployment and iterate on them as the book grows and new data sources come online

- Build and deploy predictive models build and deploy loss cost models that set pricing for Shepherd's commercial auto book

- Design and maintain feature pipelines that transform raw submission, claims, and third-party data into model-ready inputs

- Collaborate with actuaries and underwriters to translate domain expertise into model features and validate outputs against real-world outcomes

- Develop model monitoring frameworks to track drift, performance degradation, and calibration over time

- Run experiments and back-tests to quantify model impact on loss ratios, pricing accuracy, and portfolio quality

- Communicate findings clearly to technical and non-technical stakeholders through concise documentation and presentations

WHAT WE'RE LOOKING FOR

Must-Haves

- 7+ years of professional experience building and deploying personal auto or commercial lines predictive pricing models in production

- Familiarity with actuarial concepts (loss development, exposure rating, credibility)

- Strong foundation in statistics: GLMs, GBDTs, time series analysis, heavy tail distributions, and Bayesian methods

- Proficiency in Python and SQL

- ACAS/FCAS actuarial designation

- Experience with feature engineering on messy, real-world, small data

- Ability to reason from first principles and communicate results crisply to non-technical audiences

- AI-native mindset: you already use LLMs and AI tools to accelerate your own work

- Experience managing a small team or project

Nice-to-Haves

- Experience in insurance, insurtech, fintech, or other regulated industries

- Exposure to telematics pricing models

- Experience with NLP/document extraction from unstructured insurance submissions

- Prior work with model deployment infrastructure (AWS)

HOW WE WORK

Shepherd runs on four values. Here's what each one means in this seat.

- Think big, build big. We exist to protect progress and the industries that rely on it. The work here is aimed at a system that runs on its own, and the roadmap gets sequenced backward from that rather than forward from what's easy.

- Win together. We rise as one. We support each other, raise the bar, and celebrate collective success. As the first PM you set a standard the rest of the team inherits, and the milestones belong to the team rather than to product.

- Cross the aisle. Collaboration wins. We listen deeply, work across boundaries, and prioritize shared success over individual lanes. The best product calls here come from engineers who've sat with underwriters and underwriters who understand where the model breaks, and much of this job is listening closely enough on both sides to make that happen.

- Go get it. We act with urgency, move…