As a Senior Data Scientist, you'll be a key contributor to advancing our proprietary pricing excellence and solving complex business challenges across our organization. You will serve as both a technical expert and collaborative partner, helping establish Pie as the preeminent commercial insurer for small business owners through cutting-edge AI/ML solutions.
Working closely with our Data Science, ML Engineering, and Product teams, you'll develop sophisticated models and contribute to scalable systems across pricing, underwriting, and claims. Your expertise will help make AI/ML a core competency for Pie.
How You’ll Do ItWorking collaboratively with our Product, Data Engineering, and MLOps teams, you will be actively involved in the entire Model development lifecycle from conceptualization to deployment.
Advanced Model Development & Innovation
- Enhance and reinvent next-generation risk models (frequency, severity, loss ratio) and pricing models with emphasis on robustness and explainability
- Design and build AI/ML solutions for claims automation, underwriting optimization, and customer behavior analytics
- Build demand elasticity models to assess rate change impacts and optimize pricing strategies across customer segments
- Construct high-signal features from diverse internal and external data sources using advanced ML and NLP techniques
Technical Execution & Collaboration
- Conduct model diagnostics and build interpretability frameworks using cutting-edge ML methods
- Monitor model performance and develop mitigation strategies for addressing degradation
- Leverage experimentation techniques to optimize model overlays and business strategies
- Build and maintain scalable ML development pipelines supporting automation and reusability
- Support MLOps teams in deploying and testing models into production operations
- Showcase AI/ML capabilities to cross-functional teams
Technical Excellence
- Hands-on technical experience in advanced analytics, ML, or AI development and implementation
- Experience with end-to-end product development using supervised/unsupervised learning, classification, regression, clustering, and deep learning approaches
- Strong understanding of the ML lifecycle, model validation, MLOps, and modern data science tooling
- Strong experience in causal inference, experimentation, and statistical methods
Ownership & Impact
- Proven ability to deliver robust, scalable solutions in fast-paced environments
- Strong problem-solving and analytical thinking capabilities
- Excellent communication skills with ability to translate technical concepts into business insights
- Experience collaborating with cross-functional teams and stakeholders
- Growth mindset with eagerness to learn new domains and techniques
Preferred Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field required; Master's/PhD preferred
- 5+ years in advanced analytics, machine learning, or AI with 2+ years of technical ownership and leadership experience in driving projects and initiatives
- Experience in insurance, financial services, or other regulated industries
- Background in pricing models, risk assessment, or claims analytics
- Familiarity with Bayesian methods, time-series analysis, or multi-arm bandit approaches
- Experience with cloud platforms (AWS, Snowflake) and modern ML deployment practices
Foundation Building
- Learn about our business model and how we deploy analytics, ML, and AI solutions in pricing and underwriting
- Understand our data infrastructure and existing model portfolio
- Begin collaborating with underwriting and actuarial teams to identify improvement opportunities
Active Contribution
- Contribute to ongoing modeling projects while building domain expertise
- Participate in development of next-generation underwriting and pricing models
- Establish working relationships across Product, Engineering, and business teams
Ownership & Impact
- Take ownership of specific modeling initiatives and drive them to completion
- Contribute to data science best practices and workflow improvements
- Present analytical insights and recommendations to leadership
#LI-JE1
- Competitive cash compensation
- A piece of the pie (in the form of equity)
- Comprehensive health plans
- Generous PTO
- Future focused 401k match
- Generous parental and caregiver leave
- Our core values are more than just a poster on the wall; they’re tangibly reflected in our work
Our goal is to make all aspects of working with us as easy as pie. That includes our offer process. When we’ve identified a talented individual who we’d like to be a Pie-oneer , we work hard to present an equitable and fair offer. We look at the candidate’s knowledge, skills, and experience, along with their compensation expectations and align that with our company equity processes to determine our offer ranges.
Each year Pie reviews company performance and may grant discretionary bonuses to eligible team members.
Location InformationUnless otherwise specified, this role has the option to be hybrid or remote. Hybrid work locations provide team members with the flexibility of working partially from our Denver office and from home. Remote team members must live and work in the United States* (*territories excluded), and have access to reliable, high-speed internet.
Additional InformationPie Insurance is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military service status, citizenship, or other protected characteristic.
Pie Insurance participates in the E-Verify program. Please click here, here and here for more information.
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Safety First: Pie Insurance is committed to your security during the recruitment process. We will never ask you for credit card information or ask you to purchase any equipment during our interview or onboarding process.
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