National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Technical Pricing Manager

Walton, Peterborough
2 weeks ago
Create job alert

Job Title: Technical Pricing Manager

Location: Ideally working from our Peterborough office one day a week, however, depending on location we can look at a flexible approach with this.

Role purpose

We are looking for a Technical Pricing Manager to generate incremental lifetime value of our portfolio through the delivery and development of retail pricing models and optimisations using innovative and cutting-edge modelling approaches.

You will help continuously improve the pricing process and enhance the abilities of the wider team, as well as being involved with integrating and establishing the use of advanced data science and statistical techniques to enhance pricing model accuracy and output.

Key Responsibilities

End to end production of pricing models using a tailor-made pricing pipeline

Use of Earnix to build predictive statistical models and intelligently optimise customer prices

Contribute and implement improvements to the pricing process to increase pricing performance and efficiency

Contribute and lead research and development opportunities to help innovate and improve current modelling and pricing methodologies

Evaluate and utilise tools and data items created by the data science teams

Ensure all activity is compliant with pricing governance and follows established controls

Work closely with the Commercial Pricing Team to ensure pricing models meet business objectives, and manage relationships with key stakeholders around the business

Manage, mentor and coach more junior members of the team

About you:

Highly numerate with a graduate or postgraduate degree in Statistics, Mathematics or another analytical subject

Experience in a pricing or actuarial role within general insurance

Experience with price optimisation tools (Earnix/Radar)

Experience using and implementing advanced machine learning methods

Able to communicate complicated statistical concepts to an informed but non-technical audience

Experience with using software packages such as R or Python to solve problems

Proven ability to deliver commercial value through pricing insight

Proven ability to provide commercial uplift from research and development projects

Strong people management skills

About the business:

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1.2b.  The majority of business is written as the insurance pricing provider behind household names such as Co-op, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few and Markerstudy also has a large and growing direct presence in the market as well.

Having acquired and successfully integrated Co-op Insurance Services in 2021 & BGLi in 2022, Markerstudy are now pursuing innovative pricing techniques, taking advantage of an award-winning insurer hosted rating platform, whilst challenging existing embedded processes

Related Jobs

View all jobs

Technical Pricing Manager

Pricing Manager (Data Scientist) - Remote

Pricing Manager (Data Scientist) - Remote

Pricing Manager (Data Scientist) - Remote

Pricing Manager (Data Scientist) - Remote

Pricing Manager (Data Scientist) - Remote

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.