Actuarial Data Science Lead

Shepherd; Chicago (IL); On-site; USD 200,000 - 240,000; Full time

Benefits offered by this job

Premium Healthcare

Fertility benefits

Unlimited PTO

Daily lunches and snacks

Office locations: SF, NYC, Dallas-Fort

Professional development

Competitive 401(k)

Dog-friendly office

Job summary

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

Qualifications

• 7+ years of experience building and deploying pricing models in production.
• Familiarity with actuarial concepts (loss development, exposure rating, credibility).
• Strong foundation in statistics (GLMs, GBDTs, time series, heavy tails, Bayesian methods).
• Proficiency in Python and SQL.
• ACAS/FCAS actuarial designation.

Responsibilities

• Own commercial auto pricing models end-to-end from feature development through deployment and iteration as the book grows.
• Build and deploy predictive models and loss cost models for Shepherd's commercial auto book.
• Design and maintain feature pipelines transforming raw submission, claims, and third-party data into model-ready inputs.
• Collaborate with actuaries and underwriters to translate domain knowledge into model features and validate outputs.
• Develop model monitoring frameworks to track drift, performance, and calibration over time.
• Run experiments/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.

Skills

Pricing modeling

Python

SQL

ACAS/FCAS

Feature engineering

Statistics

Team leadership

Job description

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.

Our Investors

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, led our Series B round
• Costanoa Ventures, led our Series A round
• Spark Capital, led our Seed round
• Susa Ventures, lead our Pre-Seed round
• Y Combinator
• And several others

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

• 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 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

Compensation Range: $200K - $240K