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

Apply Now

Graduate Data Scientist

Manchester
10 months ago
Applications closed

Related Jobs

View all jobs

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Job Title: Graduate Data Scientist

Location: Manchester (hybrid working)

Role Overview

Markerstudy Group are looking for a Graduate Data Scientist to join a quickly growing company in developing ambitious solutions across a range of insurance lines, by leveraging vast data assets and state-of-the-art processing capabilities.

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 £1b. The majority of business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Data Scientist, you will use your advanced analytical skills to:

Identify and create cutting-edge data solutions that create value

Build and help maintain sophisticated models

Work collaboratively with other areas to increase overall company performance

Your ideas and solutions will enable improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market.

Identify and create solutions that leverage vast data assets and state-of-the-art processing capabilities to improve company performance and our customer-centric offerings. This will be across Motor, Home and Commercial Lines businesses.

Key Responsibilities:

Work collaborative with various departments to identify opportunities to create value, by optimising current processes or creating new solutions

Create ambitious future-looking solutions/models that are state-of-the-art and go beyond business requirements

Research and leverage new and existing internal and/or external data sources

Use a wide range of data science and statistical techniques, including Machine Learning

Communicate results to key decision makers across the business

Assist in the deployment and monitoring effort to ensure efficient productisation of the solutions created

Create solutions across a range of markets, including; Private Motor, Commercial Vehicle, Bike, Taxi, and Home

Key Skills and Experience:

Experience within data science

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 programming languages (e.g. Python, PySpark, SAS, SQL)

A good quantitative degree in, but not limited to: Mathematics, Statistics, Engineering, Physics, Computer Science

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

Behaviours:

Team player

Self-motivated with a drive to learn and develop

Logical thinker with a professional and positive attitude

Passion to innovate and improve processes

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.