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Data Scientist - Underwriting Analytics

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Onsite

Data Scientist - Underwriting Analytics

Insight Global

Data Scientist - Underwriting Analytics

Skills

SQL QueriesTableauPythonData ScienceRGitData AnalysisAIPower BI

17 days ago

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Important information


Contract type:

Permanent

Location:

Conshohocken, PA 19428, USA

Work mode:

Onsite

Published on:

9 October 2026

What they need


Required Skills & Experience

  • Strong grounding in mathematical statistics, actuarial science, and practical insurance/underwriting fundamentals.

  • Data science, Actuarial or actuarial-adjacent background (2+ actuarial exams passed, or an equivalent quantitative pricing credential). You'll work constantly with actuarial output, but this is not an actuarial pricing seat.

  • P&C insurance experience, commercial lines and/or MGA/program business preferred.

  • Strong SQL and Python, with hands-on GLM / predictive modeling experience applied to underwriting or pricing, not exclusively reserving.

  • Familiarity with modern data tools: version control (Git), cloud platforms, BI tools (Power BI, Tableau), or notebook environments (Jupyter).

  • You already use AI tools in your daily workflow.

Nice to Have Skills & Experience

  • Experience building a GLM in Python or R and seen it applied in underwriting practices

Job Description

Insight Global is seeking a Data Scientist for a full-time opportunity with a Specialty Insurance Provider in the Conshohocken, PA area. This person will work closely with the Underwriting team and provide predictive analytics and data findings to the respective parties across the department. This person will build the model that distributes the actuarial loss cost across real risk characteristics (building class, occupancy, TIV, geography, and beyond) and then design the underwriting levers that let the business hit that target loss ratio while staying competitive. The goal is to find creative, defensible ways to make the program more profitable. Additionally, this Data Scientist will apply modern data science techniques (predictive modeling, GLMs, gradient boosting, clustering) to build underwriting models and find segmentation opportunities the current rating plan misses. They will partner directly with Underwriting leaders to socialize findings and get guideline or lever changes adopted, not just documented.

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