Lead Data Scientist
New
Based in the United StatesFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- Graduate degree with 2+ years of experience, or 4+ years of relevant data science/analytics experience
- Required Skills
- PythonSQLMachine LearningData science
Requirements
- Graduate degree in Statistics, Mathematics, Data Science, Actuarial Science, or related quantitative field.
- 2+ years of experience with a graduate degree, 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.
Responsibilities
- 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.
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