Data Scientist

Overview

In this role you will apply a broad set of analytics techniques to solve real-world insurance problems. You will work with cross-functional teams to operationalize models across cutting-edge platforms, leveraging AI, ML, and statistics on data from multiple sources. You’ll help build reusable analytics assets and collaborate with engineering to deploy solutions that scale across lines of business and geographies. This is a hands-on position that combines hands-on modeling with clear communication to business partners. You will contribute to a data-driven, collaborative analytics culture at Chubb.

Pay / Benefits

• competitive salary
• pension scheme
• discretionary bonus scheme
• hybrid working options
• Private Medical cover
• Employee Share Purchase Plan

Responsibilities

• Partner with Product Owners, Data Scientists, Engineers, and Project Managers on modeling projects and new use cases for Global Analytics Technology Platforms
• Execute all aspects of analytics initiatives including exploratory data analysis, model development, evaluation, and benefit estimation
• Build reusable frameworks and automate assets for analytics teams; emphasize reproducibility
• Foster strong working relationships with business partners, IT, and analytics peers
• Effectively communicate results in written, oral, and presentation formats
• Monitor model performance and report findings to stakeholders

Key requirements

• 3+ years of analytics experience (Data Scientist, ML Engineer, Data Analyst, etc.)
• Bachelor’s or Master’s degree in a related field
• Programming in Python (OOP)
• SQL for data extraction and manipulation
• Experience with ML and statistical model development and deployment
• Strong communication skills for technical and non-technical audiences
• Experience with GitHub, Python, Databricks, VSCode, MLFlow
• Experience using AI tools such as Claude Code

• strong communication
• ability to translate technical topics for non-technical stakeholders
• cross-functional collaboration
• Python
• SQL
• Machine Learning

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