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# Data Scientist - QPS

- **Company:** QBE Insurance Group Limited
- **Location:** London, United Kingdom (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Process Modeling, Collaborative Software, Python (Programming Language), Machine Learning, SQL Databases, Value Engineering, Feature Engineering, Machine Learning Operations, Software Version Control, Databricks
- **Published:** November 8, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/data-scientist-qps/55391703

## About the Role

You may bring experience from either of the following routes:
Pricing or actuarial: commercial insurance pricing, portfolio analytics, GLMs, rate adequacy, risk selection or portfolio performance, supported by strong analytical and coding skills.
Data science or machine learning: predictive modelling, feature engineering, ML pipelines, workflow automation or MLOps, ideally using Python, SQL and Databricks.

What You Will Bring:
Strong analytical and problem-solving skills, with practical experience in pricing, statistical modelling or machine learning.
Strong Python skills and confidence working with data; SQL experience is highly desirable.
Knowledge of reproducibility, testing, version control and good software or ML engineering practices.
Ability to work with technical teams and business stakeholders and explain complex analysis clearly.
Interest in applying machine learning to real commercial problems.

Experience in commercial or specialty insurance would be an advantage., Adaptability, Administration Management, Analytical Thinking, Business Process Modeling, Collaboration Tools, Communication, Critical Thinking, Customer Value Management, Insurance Underwriting, Intentional collaboration, Managing performance, Policy Documentation, Presenting with Impact, Risk Management, Stakeholder ManagementHow to Apply

## Description

Join QBE Portfolio Solutions (QPS) in our Scout: Research & Insights team. You will use pricing, data science and machine learning to improve underwriting and portfolio decisions.
We welcome candidates from either an insurance pricing or actuarial background , or a data science and machine learning background . You will combine commercial understanding, modelling and technology to create scalable analytical solutions.
Your New Role
Develop pricing, statistical and machine-learning models for underwriting and portfolio decisions.
Analyse policy, exposure, claims and pricing data to identify trends, risks and opportunities.
Build reusable solutions using Python, SQL and Databricks .
Apply sound ML engineering practices so models are reproducible, tested, maintainable and ready to operationalise.
Work with underwriting, pricing, catastrophe modelling, Data & AI and engineering teams to turn business questions into scalable solutions.
Communicate complex analysis as clear insights and recommendations for technical and non-technical stakeholders.