Pricing Data Science Lead- SME

QBE Europe
City of London
4 months ago
Applications closed

Related Jobs

View all jobs

Data Science Lead

MOTOR INSURANCE PRICING PRACTITIONER / DATA SCIENTIST

MOTOR INSURANCE PRICING PRACTITIONER/DATA SCIENTIST

Senior Data Scientist

Trainee Data Analyst

Trainee Data Analyst

Primary Details: Time Type: Full time, Worker Type: Employee. We are seeking a highly analytical and commercially astute Lead Pricing Data Scientist Analyst to join our growing E-trade team. This senior role is pivotal in shaping our pricing strategy and portfolio performance across multiple lines of business (Property, Casualty, Financial Lines and Motor).

Pricing Data Science Lead – SME Motor

Location: London/Manchester/Stafford/Birmingham/Hybrid

The Opportunity:

We are seeking a highly analytical and commercially astute Lead Pricing Data Scientist Analyst to join our growing E-trade team. This senior role is pivotal in shaping our pricing strategy and portfolio performance across multiple lines of business including Property, Casualty, Financial Lines and Motor. You will lead a small team of analysts and work closely with underwriting, actuarial, and senior leadership to drive profitable growth and ensure pricing adequacy and competitiveness.

With hybrid office working and excellent benefits including 30 days holiday, you will be working in a supportive and inclusive environment.

Your Role:
  • Lead and mentor a team of Pricing and Portfolio Analysts, fostering a culture of excellence and collaboration.
  • Support team growth through coaching, training, and performance reviews.
  • Define clear accountabilities and drive a high-performance culture.
  • Develop and maintain pricing models across Property, Casualty, Financial Lines, and Motor.
  • Lead pricing reviews and recommend rate changes based on performance and market trends.
  • Collaborate with Underwriting to align pricing tools with strategy.
  • Monitor portfolio performance, identify risks/opportunities, and produce MI reports for stakeholders.
  • Recommend actions to optimise profitability and risk selection.
  • Champion data science and automation in pricing and portfolio analysis.
  • Evaluate and implement new tools, data sources, and methodologies.
About you:
  • Proven experience in general insurance pricing or portfolio analysis, with strong analytical and strategic capabilities.
  • Exposure to multiple lines of business, including Property, Casualty, Financial Lines, and Motor.
  • Demonstrated ability to deliver pricing improvements and actionable portfolio insights.
  • Strong leadership, stakeholder engagement, and communication skills.
  • Proficiency in pricing tools and data platforms (e.g., SQL, Python, Power BI), with commercial awareness.
  • Comfortable navigating regulatory frameworks and managing competing priorities under pressure.
Benefits
  • 30 days holiday a year with the option to buy up to 2 additional days.
  • Flexible working - balancing work and life is important so our flexible working opportunities are open to all.
  • Pension – you are automatically enrolled into the QBE pension plan, which entitles you to receive employer contributions of 10% of your basic salary.
  • Private medical insurance – we fund fully comprehensive private medical cover for you and all the family.
  • Family friendly policies – we offer 26 weeks leave at full pay regardless of gender identity, sexual orientation or how you become a parent.
Equal Employment Opportunity

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


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.