• Shepherd is an AI-native commercial insurance platform focused on transforming insurance for high-hazard industries, aiming to make risk frictionless for builders and operators of physical infrastructure.
• The company addresses inefficiencies in traditional commercial construction insurance, using AI to perform underwriting workflows in seconds and integrating real-time data from construction technology partners.
• Shepherd's technical vision is fully autonomous underwriting, aiming for agent-free submissions and pricing.
• Benefits of Shepherd's approach include faster decisions, smarter pricing, and better risk outcomes.
• Investors include Intact Private Capital (lead investor and carrier partner), Spark Capital, Costanoa Ventures, Y Combinator, Susa Ventures, among others.
• The team consists of technologists and insurance enthusiasts.

Actuarial Data Scientist Role:

• Location: San Francisco; Chicago; New York City (On-site)
• Employment Type: Full time
• Department: Actuarial
• Compensation: $160K – $200K plus stock options, unlimited PTO, 100% medical/vision/dental coverage

Responsibilities:

• Own commercial auto pricing models end-to-end from feature development through deployment.
• Build and deploy predictive loss cost models for commercial auto insurance.
• Design and maintain feature pipelines transforming raw data into model inputs.
• Collaborate with actuaries and underwriters to incorporate domain expertise.
• Develop model monitoring frameworks to track performance over time.
• Run experiments/back-tests to measure model impact on loss ratios and pricing accuracy.
• Communicate findings clearly to technical and non-technical stakeholders.

Requirements:

• 3+ years experience building/deploying personal auto or commercial lines predictive pricing models.
• Familiarity with actuarial concepts (loss development, exposure rating, credibility).
• Strong statistics foundation (GLMs, GBDTs, time series analysis, heavy tail distributions, Bayesian methods).
• Proficiency in Python and SQL.
• Experience with feature engineering on messy real-world data.
• Ability to communicate results crisply to non-technical audiences.
• AI-native mindset using LLMs/AI tools to accelerate work.

Nice-to-haves:

• Experience in insurance/insurtech/fintech.
• Telematics pricing models experience.
• NLP/document extraction from unstructured submissions.
• AWS model deployment infrastructure experience.

Benefits:

• Premium healthcare fully covered (health, dental, vision).
• Fertility benefits and family building support.
• Unlimited PTO.
• Daily meals provided at office locations (SF, NYC, Dallas-Fort Worth, Chicago, LA).
• Professional development including leadership coaching.
• Competitive 401(k) plan.
• Dog-friendly office environment.