Pricing Data Scientist

Primary Details

Time Type: Full time

Worker Type: Employee

This role focuses on developing and deploying data science solutions to support SME commercial insurance pricing, underwriting decisions, and portfolio optimisation.

Pricing Data Scientist

London/Stafford - Hybrid

About QBE

At QBE, we get to the heart of what matters for our customers. And we do it all with a human touch.

We’re an international insurer with more than 13,000 people working across 26 countries – which means we’re big enough for your ambitions, yet small enough for you to make a real impact. It’s an exciting time. We’re building momentum towards our vision to become the most consistent and innovative risk partner.

What if you could have a positive impact – at work and in the world? As part of the QBE team, you’ll get to spend every day working with people who are passionate, talented and kind.

The Opportunity

As a Pricing Data Scientist at QBE, you will play a key role in shaping how we use data to drive smarter pricing decisions and deliver better outcomes for our customers. Sitting at the heart of our underwriting and pricing function, you’ll combine advanced analytics with commercial insight to influence strategy, improve portfolio performance, and support innovation across the business. You’ll work closely with stakeholders across underwriting, pricing, and data teams, helping translate complex data into clear, actionable insights while contributing to the development of next-generation pricing capabilities.

Your new role

Identify and prioritise high-value analytical opportunities that drive measurable improvements in pricing performance (including loss ratio, growth, and retention)

Lead discussions with business stakeholders to identify how data science can improve decision-making and outcomes

Develop and deploy predictive models to support pricing and underwriting decisions, including risk cost modelling, demand modelling, and price optimisation

Translate model outputs into clear pricing recommendations and insights that influence underwriting and portfolio decisions

Monitor and evaluate model performance, defining refresh and recalibration requirements

Design and prototype analytical tools and applications for business users (e.g. underwriters, claims handlers)

Work closely with data engineering and data platform teams to source, structure, and prepare data for modelling

Lead the development of new analytical propositions to enhance core insurance functions

Lead analytical projects and coordinate delivery across teams

Mentor junior team members and support their development

About you

Insurance experience is preferred but not essential

Strong knowledge of statistical / data mining methods and application in a business environment

Good understanding of Data Science domain, statistical and analytical model development and implementations, proficient in GLMs, machine learning techniques and related disciplines

Good understanding of data modelling techniques, tools/language – (preferably Python) .

Good knowledge of visualization tools like PowerBI, Tableau etc.

Experience of insurance pricing tools (such as Emblem and Radar) is preferred but not essential

Skills:

Communication, Critical Thinking, Data Science, Data Visualization, Financial Products, Innovation, Intentional collaboration, Machine Learning (ML), Managing performance, Mentorship, Research Analysis, Risk Management, Stakeholder Management, Team Management, Thought Leadership

How to Apply:

To submit your application, click "Apply" and follow the step by step process.