Shepherd
Actuarial Data Science Lead
1w ago
200000 –240000 USD / yearUSALeaddata scienceactuarial modelingmachine learningpythonai
Lead data science efforts in actuarial modeling for an AI-native commercial insurance platform.
About the company
- We're a team of technologists and insurance enthusiasts, bridging the two worlds together. Check out our About page to learn more.
Responsibilities
- 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.
- 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
Requirements
- 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 have
- 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)
Conditions
- 🏥 Premium Healthcare 100% contribution to top-tier health, dental, and vision
- 🥕 Fertility benefits and family building support
- 🏖️ Unlimited PTO Flexibility to take the time off, recharge, and perform
- 🥗 Daily lunches, dinners, and snacks We work together, and enjoy meals together too
Other
- Shepherd is an AI-native commercial insurance platform transforming how high-hazard industries get covered. 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.
- The infrastructure behind the AI boom — data centers, semiconductor fabs, renewable energy assets — has to be built and insured. But traditional carriers weren't built for this speed:
- Complex commercial construction projects routinely wait weeks for a single quote
- Legacy carriers rely on static applications and disconnected systems
- Brokers chase carriers through calls, emails, and resubmissions
- We built Shepherd to solve that. Our AI performs the same underwriting workflows in seconds, and integrates real-time data from construction technology partners — Procore, Autodesk, OpenSpace, DroneDeploy, and others — to see risk as it actually exists, not just as it was reported on a static form.
- We're pursuing the most ambitious technical vision in commercial insurance: fully autonomous underwriting. We're closing in on the first fully agentic submission in the industry — email in, price out, no human intervention until the last mile.
- With Shepherd, safety, speed, and quality no longer trade off against one another — they compound. We're building:
- Faster decisions
- Smarter, more accurate pricing
- Better risk outcomes for insureds who invest in safer practices
- We're not just modernizing insurance products. We're building the risk infrastructure for the next generation of financial services.
- In March 2026, Shepherd raised a $42M Series B — 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
- Spark Capital
- Costanoa Ventures
- Y Combinator
- Susa Ventures
- And several others
- 📚 Professional Development Access to premium coaching, including leadership development
- 🐶 Dog-friendly office Plenty of dogs to play with and make friends with in the SF office