Data Scientist / Junior Data Scientist (Python, Pandas)

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

Job summary

A leading recruitment agency is seeking a Data Scientist or Junior Data Scientist to work in a hybrid role, primarily in Bristol. The successful candidate will have strong Python and Pandas skills and will be involved in cleaning and preparing insurance portfolio data. This position offers a salary range of £40,000 - £45,000, with up to £50,000 for exceptional candidates. Interested applicants should send their CV to a designated email address.

Qualifications

• 2-4 years in a data-driven or technical role.
• Strong skills in Python and Pandas required.
• Experience in data ingestion using ETL pipelines.

Responsibilities

• Clean, validate, and standardise large datasets using Python.
• Develop tools for data cleaning workflows.
• Generate data reports related to insurance risk.

Skills

Strong skills in Python

Pandas expertise

Data validation and cleaning

ETL pipelines experience

Attention to detail

Tools

Databricks

Git

PySpark

SQL

Job description

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 [e-mail] - I'd love to hear from you!