Data Scientist (Python, Pandas)

Adecco; Scotland; Hybrid; GBP 50,000; Full time

Job summary

A recruitment agency is seeking a skilled Data Scientist for a hybrid position in the UK, involving the cleaning and processing of insurance data using Python and Pandas. Ideal candidates will have 2-4 years of experience in data-driven roles, possess strong analytical skills, and a keen attention to detail. This role offers competitive salary and the chance to make impactful decisions in cyber risk modelling.

Qualifications

• 2-4 years in a data-driven or technical role.
• Commercial experience blending data engineering and data science approaches.
• Curious, adaptable, and a natural problem solver.

Responsibilities

• Clean, validate, and standardise large insurance datasets using Python (especially Pandas).
• Generate insightful data reports related to insurance exposure and risk events.
• Continuously improve data workflows, quality, and ingestion pipelines (ETL).

Skills

Python

Pandas

Attention to detail

Data quality

Tools

Databricks

Git

PySpark

SQL

Job description

Data Scientist - Hybrid (Bristol-based)

GBP40,000 - GBP45,000 (up to GBP50,000 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!