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

Apply Now

Senior Pricing Analyst

Manchester
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Sales Account Manager / Director - Enterprise Cloud Data Tech

Senior Sales Account Manager / Director - Enterprise Cloud Data Tech

Senior Sales Account Manager / Director - Enterprise Cloud Data Tech

Senior Data Engineer

Senior AWS Data Engineer

Senior Data Engineer

Job Title: Senior Pricing Analyst

Locations: Manchester (flexible)

Role Overview

Markerstudy Group are looking for a Senior Pricing Analyst to help build and shape our pricing models. You will help monitor our portfolio and deliver innovative pricing solutions within the Retail Pricing team.

Joining our retail pricing team, you will be keeping a close eye on trading across different channels and insurance products. You will have previous experience in general insurance pricing and be familiar with the tools of the trade, such as SAS, Python, RStudio, SQL, Emblem and Radar. With your naturally inquisitive mindset, you will be well versed in the UK personal lines insurance space, and understand how the personal lines insurance market works. Always open to change, you have a keen eye for the continuous improvement of process.

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

Conducting retail price optimisation analysis/modelling

developing customer propensity and Life Time Value (LTV) models to produce the different models and SAS or SQL for data analysis

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

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

Advance the adoption of data science & statistical techniques

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

Collaborate with peers in pricing, underwriting and data science

will generate insight to help make commercial decisions and strategic changes to prices to meet budget requirements.

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

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.

The Best Free Tools & Platforms to Practise Data Engineering Skills in 2025/26

Data engineering has rapidly become one of the most critical disciplines in technology. Every business, from financial services to healthcare to e-commerce, relies on robust data pipelines to move, transform, and store information efficiently. Without skilled data engineers, the modern data-driven economy would grind to a halt. The challenge for job seekers? Employers don’t just want to see academic credentials. They want hands-on evidence that you can build and manage data workflows, integrate sources, optimise performance, and deploy solutions at scale. Fortunately, you don’t need expensive software licences or premium courses to gain practical experience. A wealth of free tools and platforms allow you to practise and master the essential skills of a data engineer. In this vlog-style guide, we’ll cover the best free resources you can use in 2025 to build portfolio-ready projects and boost your job prospects.

Top 10 Skills in Data Engineering According to LinkedIn & Indeed Job Postings

Data engineering is the backbone of modern analytics, AI, and business intelligence. Across the UK—from finance and health to e-commerce and public sector—organisations are investing heavily in platforms that ingest, process, and store vast amounts of data. Demand for professionals who can build robust, scalable, and reliable data pipelines has never been higher. But what skills do employers really want? By analysing job postings on LinkedIn and Indeed, this article highlights the Top 10 data engineering skills that UK organisations are looking for in 2025. You’ll learn how to surface these skills in your CV, demonstrate them in interviews, and build proof-of-work through a compelling portfolio.

The Future of Data Engineering Jobs: Careers That Don’t Exist Yet

Data engineering has quietly become one of the most crucial roles in modern technology. While data science and artificial intelligence often attract the headlines, it is data engineering that provides the foundation. By building pipelines, managing databases, and ensuring data quality, data engineers make it possible for organisations to analyse, innovate, and grow. In the UK, data engineering is booming. Banks rely on engineers to process financial transactions in real time. Retailers depend on them to analyse customer behaviour. Healthcare providers use engineered data to fuel predictive analytics in the NHS. Demand is so strong that data engineering has become one of the fastest-growing roles in the tech sector, with salaries reflecting its importance. But the story doesn’t stop here. As AI, quantum computing, edge intelligence, sustainability, and regulation reshape how we manage information, the role of data engineers will evolve dramatically. Many of the most important data engineering jobs of the next two decades don’t exist yet. This article explores why new roles are coming, what they might look like, how current jobs will change, why the UK is positioned to lead, and how professionals can prepare.