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

Apply Now

Principle Pricing Analyst

Manchester
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Pricing

Senior Data Scientist

Senior Pricing Data Scientist

Senior Pricing Data Scientist

Senior Pricing Data Scientist

Data Scientist - Borrow Analytics Manager

Job Title: Principle Pricing Analyst

Locations: Manchester (flexible)

Role Overview

This role is for Atlanta Group, part of the Markerstudy Group.

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

You will Utilise your technical expertise, in-depth knowledge of insurance industry and market leading tools to produce creative and actionable pricing solutions. This is to maximise Atlanta’s ability to meet its strategy and annual plan but should also influence that strategy through regular identification of opportunities to Pricing Managers, Head of Pricing and Executive Committee. This role requires a large element of coaching team members and championing best practice across the department.

Reporting to the Head of Pricing, you will make use of WTW Radar and Emblem and you will have responsibility for the development and maintenance of predictive models (GLM) and price optimisation including machine learning algorithms (GBM), LTV (Lifetime Value) and fair pricing principles. Ultimately creating value for our customers and Atlanta.

Bringing best in class pricing experience, you’ll be expected to provide pricing proposals considering customer and commercial outcomes, communicating these in a compelling, impactful way to all levels of stakeholders to help us make the right decisions at the right times.

You’ll work on multiple priorities within a fast paced, dynamic environment. You’ll need to be able to manage the expectations of stakeholders alongside prioritising your workload.   

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

Be a key stakeholder influencing the direction & outcome of projects

Provide technical leadership on WTW toolkit (in particular Radar Optimiser) to drive forward effective and efficient solutions

Provide thought leadership on optimisation and modelling concepts

Research, develop and champion the use of best practice methods and standards and ensure they are embedded throughout the department

Lead the development of the Groups pricing capability

Query large databases to extract and manipulate data that is fit for purpose

Oversee and assist in the development and implementation of the market leading methodologies you've identified

Deliver regular management information on specific KPI's relating to Atlanta's performance

Continuously evaluate methodologies, understanding how they fit into the wider piece, and identify where they can be improved

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 good 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

Personality and a sense of humour

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.