Data Scientist (Python, Pandas)

Data Scientist - Hybrid (Bristol-based)

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

Hybrid Working | Python & Pandas

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 modelling using advanced stochastic techniques, and they're on the lookout for a skilled 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 Python skills with a deep understanding of Pandas Excellent attention to detail and a strong sense of data quality Commercial experience blending data engineering and data science approaches Experience with data ingestion and ETL pipelines 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 (see below) - I'd love to hear from you!