Job Details

Position: Data Scientist

Location: Conshohocken, PA 19428 – hybrid onsite 1-2 days a week

Duration: Perm, direct hire

Salary: $110,000 - $150,000/year

Required Skills & Experience

• 2-3+ years of experience in a data science, analytics, or quantitative research role — experience in the P&C insurance space (carrier, MGA, broker, or insurtech) strongly preferred.
• Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Actuarial Science, or Economics); Masters degree is a plus.
• Strong proficiency in Python and/or R for statistical analysis and model development.
• Advanced SQL skills and proven ability to work with large, complex relational datasets across multiple source systems.
• Hands-on experience building and deploying predictive models beyond proof-of-concept — including documentation, monitoring, and stakeholder handoff.
• Working knowledge of core P&C insurance concepts: premium, loss ratio, combined ratio, and policy lifecycle.

Job Description

• Insight Global is seeking a Data Scientist for a full-time opportunity with a Specialty Insurance Provider, in the Conshohocken, PA area. The Data Scientist will work closely with underwriting, product, operations, and leadership teams and expected to own problems end-to-end. The Data Scientist will operate with a high degree of independence while collaborating closely with cross-functional stakeholders. This role draws on the type of work seen across the broader insurance ecosystem. This role will report to the SVP, Data & AI. This Data Scientist will partner with engineering and IT to build and maintain reliable data pipelines from multiple sources, including policy admin systems, claims platforms, and third-party data enrichment providers (e.g., LexisNexis, Verisk, CoreLogic). Additionally, they will analyze submission, bind, and quote data to identify trends in hit ratio, declination patterns, and appetite alignment. They will also support pricing analysis and adequacy reviews in collaboration with actuarial resources or carrier partners, using exposure-normalized loss data. Lastly, this person must develop customer lifetime value (LTV) and retention models to support renewal strategy and identify at-risk accounts before they lapse, and will analyze distribution partner performance data to identify growth opportunities, cross-sell potential, and capacity allocation priorities.