Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Technical Pricing Manager

Walton, Peterborough
5 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Retail Pricing)

Senior Data Scientist

Lead Machine Learning Engineer

Data Science Manager

Principal Product Manager, Data Science & Machine Learning

Principal Product Manager, Data Science & Machine Learning

Job Title: Technical Pricing Manager

Location: Peterborough (flexible hybrid working)

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

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.