Location
London or Reigate office. Your office location will be agreed with you during the onboarding process. You may be expected to travel to other WTW locations for team or client meetings.

Hours
Full time, with an expectation to be in the office at least four days a week to support in-person learning and collaboration.

Salary
Negotiable

About the Role
Join WTW’s Insurance Consulting and Technology (ICT) team and be part of impactful projects from day one. Our ICT team combines deep insurance consulting expertise with innovative technology, working across major actuarial pillars within Property and Casualty (P&C) including reserving, capital, and pricing, as well as broader areas such as data science, process transformation, risk and regulatory, climate, exposure management, underwriting, and claims analytics. You will work on client projects, research, and product development, using data science techniques to analyse data and produce insightful results. Responsibilities include presenting analysis internally and to clients, collaborating with UK and global colleagues, building core technical skills through hands-on experience, delivering data science projects involving machine learning model development and deployment, and using both open-source tools and WTW’s proprietary insurance technology solutions. You will also benefit from structured early-career training and ongoing learning from subject matter experts.

Experience
Experience in a coding or data-processing language such as Python, R, SQL or similar is required. Exposure to concepts such as Retrieval-Augmented Generation ("RAG") and Agentic AI is beneficial but not essential.

About you
Highly numerate and analytical with a strong interest in extracting value from data and solving complex commercial problems. Genuinely interested in recent advancements in data science, including Machine Learning and Generative AI. Clear and confident communicator able to explain complex ideas to diverse audiences. Personable, approachable, motivated, and a team player. Interested in learning and developing new ideas. Comfortable using AI tools with an understanding of their strengths and limitations.

Qualifications
At least a 2:1 degree in a numerate discipline. A-level Mathematics at grade A or above. At least 136 UCAS points across three A levels or equivalent qualifications (e.g., AAB or A*AC meets the points requirement).