United States
HEARTLAND BUSINESS SYSTEMS LLC
Shepherd
Actuarial Data Science Lead
United States
San Francisco, California, United States · Chicago, Illinois, United States · New York, New York, United States
PythonSQLAWSGo
What We Do
Commercial insurance still runs on processes built decades ago. Underwriting is slow, and pricing leans on broad averages instead of the specifics of each risk. Technology can change how commercial risk is priced and managed, as long as it's paired with real underwriting expertise. The companies that get this right will shape the next era of the industry, and Shepherd intends to lead it.
Shepherd is a Managing General Underwriter (MGU) building the fastest and smartest AI-native commercial risk platform in the industry, where underwriters, data, and automation work together. The result is faster decisions for our broker partners and pricing that reflects the actual risk.
We started where the gap is widest: construction and energy, two of the most complex and highest-hazard segments in commercial insurance. Today we write Primary and Excess Casualty, Builder’s Risk, and Workers' Compensation distributed through a nationwide network of retail brokers. Our mission is to make risk frictionless for the builders and operators shaping the physical world, from concept through construction and into decades of operation.
🚀 Our Investors
Shepherd has raised over $67M, including a $42M Series B led by Intact Private Capital. Intact also partners with Shepherd to provide capacity across its insurance products. Shepherd is also backed by leading institutional investors, including Costanoa Ventures, Spark Capital, Susa Ventures, and Y Combinator.
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. Come set a standard the rest of the team inherits.
- 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 with confidence, take smart risks, and push forward with intention. Nobody hands you the roadmap, the data, or the meeting invite. You pull the failing runs, book the time with the underwriters, and decide what matters.
Benefits
- 🏥 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
- 🖥️ SF, NYC, Dallas-Fort Worth, Chicago and LA Offices
- 📚 Professional Development Access to premium coaching, including leadership development
- 🏦 Competitive 401(k) Plan
- 🐶 Dog-friendly office Plenty of dogs to play with and make friends with in the SF office
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