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

Apply Now

Senior Pricing Analyst

Haywards Heath
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Pricing

Senior Data Scientist

Data Scientist - Retail Price Optimisation - Motor

Senior Data Scientist

Senior Data Scientist

R&D Senior Data Scientist

Job Title: Senior Pricing Analyst

Locations: Haywards Heath or Manchester (Hybrid)

Role Overview

Markerstudy Group are looking for a Senior Pricing Analyst to join a quickly growing and developing pricing department across a range of insurance lines.

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.

As a Senior Pricing Analyst, you will use your advanced analytical skills to:

Be a key stakeholder influencing the direction & outcome of projects across a range of personal lines products.

Create innovative data solutions finding new ways to mine insight & present data.

Build and maintain sophisticated models, prioritising a range of data science techniques.

Develop reporting structures to monitor pricing performance in an automated fashion.

Working with the retail pricing teams and closely with underwriting teams, your insight and recommendations will enable improvements to products and prices giving Markerstudy a critical advantage in the increasingly competitive insurance market.

Key Responsibilities:

Develop a suite of advanced pricing models using a combination of traditional & data science techniques across Private Car, Commercial Vehicle & Home accounts.

Advance the adoption of data science & statistical techniques across pricing & underwriting.

Research and leverage new and existing data sources; capturing and explaining trends with innovative data features.

Communicate results to key decision makers across the business for action based on the results of pricing analysis.

Review observed & expected performance of key accounts.

Collaborate with peers in pricing, underwriting and data science.

Facilitate automation of repeatable tasks.

Using specialist software to monitor trends and review impact of pricing proposals.

Coaching and mentoring team members.

Key Skills and Experience:

Previous experience within general insurance pricing.

Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering.

Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL).

A quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science).

Experience of WTW’s Radar software is preferred.

Proficient at communicating results in a concise manner both verbally and written.

Behaviours:

Self-motivated with a drive to learn and develop.

Logical thinker with a professional and positive attitude.

Passion to innovate, improve processes and challenge the norm

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.