Data science jobs in Insurance industry

Data Science in Insurance

Insurance is data-driven by design. Actuarial tradition is being extended by modern data science to build more granular pricing models, automate claims assessment, detect fraud, and personalise customer retention campaigns.

Common roles

Actuarial data scientists, claims fraud analysts, pricing model engineers, and customer propensity modellers are common. Telematics and IoT analytics roles are growing in motor and home insurance.

Key skills

Python, R, generalised linear models, gradient boosting (XGBoost, LightGBM), survival analysis, SQL, and familiarity with regulatory constraints such as Solvency II are valued across the insurance sector.