Company
Insurance
LeadDataScientist
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Data Scientist. Skills: Pricing models, Machine learning, Statistical techniques, Data analysis. Lead development of GLM-based pricing models. Refine GLM-based pricing models”
What You'll Achieve.
Improve predictive accuracy; Improve customer behavior insights; Improve portfolio performance
Industry & Context.
Problem-solving abilities
What They're Looking For.
Must Have
Graduate degree in Statistics, Mathematics, Data Science, Actuarial Science, or related quantitative field, 2+ years of experience, 4+ years of relevant data science/analytics experience, 1 year of experience in P&C or pet insurance pricing, Proficiency in Python and SQL, Deep understanding of generalized linear models (GLMs), regression techniques, and statistical inference methods, Ability to manage multiple high-impact projects simultaneously, Communication skills
Nice to Have
PhD preferred, Experience with Snowflake, Databricks, SQL Server, or data warehousing environments, Familiarity with WTW Radar, Emblem, or Earnix, Familiarity with dashboarding tools like Power BI
What You'll Do.
Lead development of GLM-based pricing models
Refine GLM-based pricing models
Maintain GLM-based pricing models
Apply machine learning techniques
Apply advanced statistical techniques
Conduct deep exploratory data analysis
Conduct root-cause investigations
Collaborate with engineering teams
Ensure high-quality inputs for modeling
Translate complex modeling outputs
Serve as subject matter expert in insurance pricing
Support methodological rigor
Support analytical best practices
Mentor junior data scientists
Contribute to development of scalable data science standards
Contribute to development of scalable data science practices
How You'll Work.
Team & Collaboration
Cross-functional environments; Actuarial teams; Product teams; Engineering teams
Communication Scope
Explain complex analytical concepts; Actionable insights
Process & Methodology
Manage concurrent initiatives, Manage multiple projects
Full Job Description
## Accountabilities Lead the development, refinement, and maintenance of GLM-based pricing models and related statistical approaches used for insurance rate setting and risk segmentation. Own end-to-end delivery of analytical projects, independently managing 2–4 concurrent initiatives across pricing, research, and model enhancement. Apply machine learning and advanced statistical techniques to improve predictive accuracy, customer behavior insights, and portfolio performance. Conduct deep exploratory data analysis and root-cause investigations using Python and SQL to support pricing and business decisions. Collaborate with engineering teams to resolve data issues and ensure high-quality inputs for modeling and analytics. Translate complex modeling outputs into clear, actionable insights for both technical and non-technical stakeholders, including senior leadership. Serve as a subject matter expert in insurance pricing, supporting methodological rigor and analytical best practices across the team. Mentor junior data scientists and contribute to the development of scalable data science standards and practices. Requirements: Graduate degree in Statistics, Mathematics, Data Science, Actuarial Science, or related quantitative field with 2+ years of experience, or 4+ years of relevant data science/analytics experience. At least 1 year of experience in P&C or pet insurance pricing, including rate modeling, GLMs, or actuarial/data science applications. Strong proficiency in Python and SQL for data manipulation, modeling, and advanced analysis. Deep understanding of generalized linear models (GLMs), regression techniques, and statistical inference methods. Proven ability to manage multiple high-impact projects simultaneously in a fast-paced, collaborative environment. Strong communication skills with the ability to explain complex analytical concepts to diverse audiences. Experience working in cross-functional environments with actuarial, product, and engineering teams. Stro
Applying for this Lead Data Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.