Data Scientist or Junior Data Scientist - Hybrid (Bristol-based 2-3 days a week) Insurance

💼 £40,000 - £45,000 (up to £50,000 for exceptional candidates)

Strong skills in Python & Pandas with at least 2 years experience in a commercial Data Driven role

Are you passionate about data and ready to make a real impact in the world of cyber risk?

We're working with a forward-thinking company that's pioneering cyber risk using advanced stochastic techniques, and they're on the lookout for a Data Scientist or Junior Data Scientist to join their growing team. This is a brilliant opportunity for someone with a sharp analytical mind and solid Python skills, who enjoys building efficient data pipelines and uncovering insights from complex datasets.

🔍 The Role

You'll play a key role in cleaning, enriching, and preparing insurance portfolio data that feeds into cutting-edge risk models. From day one, you'll work closely with modellers, data scientists, and engineering experts to ensure high data quality and process efficiency. The work you do will directly influence insights into cyber exposure and risk trends.

🛠️ Key Responsibilities

Clean, validate, and standardise large insurance datasets using Python (especially Pandas)

Develop and refine internal tools and utilities for data cleaning workflows

Support the integration of LLMs to automate data prep, including prompt engineering and model evaluation

Generate insightful data reports related to insurance exposure and risk events

Communicate findings clearly to both technical and non-technical teams

Apply software engineering practices to improve data systems and pipelines

Continuously improve data workflows, quality, and ingestion pipelines (ETL)

Stay ahead of trends in data science, reinsurance, and cyber risk

🎯 What We're Looking For

2-4 years in a data-driven or technical role
Strong skills in Python and Pandas is a must
Data ingestion using ETL pipelines experience
A background in financial services is preferred, but not essential.
Insurance experience a bonus
Excellent attention to detail and a strong sense of data quality
Commercial experience blending data engineering and data science approaches
Curious, adaptable, and a natural problem solver

Bonus points for:

Experience in financial services, insurance, or reinsurance

Familiarity with Databricks, Git, PySpark or SQL

Exposure to cyber risk or large-scale modelling environments

📩 Ready to Apply for this exciting Data Scientist role?

Send your CV to (url removed) - I'd love to hear from you