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Pricing Data Scientist

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: 慨正橡扯
Full Time position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Machine Learning/ ML Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

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.

Responsibilities
  • 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
Qualifications
  • 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

Equal Employment Opportunity

QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.

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