Data Analyst

Job title: Data Analyst

Locations: Manchester (hybrid working)

Role overview

As a Data Analyst at Markerstudy, you will contribute to the delivery of analytics solutions that support strategic decision-making across our insurance brands. Working within the Analytics & Enrichment team, you’ll help generate insights that improve insurer panel performance collaborating with teams across pricing and insurer relations.

This role is ideal for someone with a strong analytical foundation, a passion for data, and a desire to grow their technical and commercial skills in a fast-paced, data-driven environment.

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. Most of Markerstudy’s 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.

Key Responsibilities

• Deliver high‑quality analysis: Produce accurate, timely insights that support day‑to‑day business decisions.
• Answer business questions with data: Analyse datasets to explain performance, identify trends, and highlight opportunities or risks.
• Collaborate with stakeholders: Work with partners to understand requirements, clarify questions, and respond to feedback.
• Maintain reporting and dashboards: Build, refresh, and monitor reports tracking key metrics and KPIs.
• Support analytical models and processes: Contribute to the development, testing, and ongoing monitoring of existing models such as marketing selection models.
• Continuously develop analytical skills: Build technical and business knowledge, staying curious and open to new tools and techniques.

Key Skills and Experience

• Strong academic background in a numerical discipline (eg BSc Mathematics, Computer Science, Data Science).
• Proficiency in SQL and working knowledge of Python and/or R.
• Understanding of statistical and machine learning techniques (e.g. regression, clustering).
• Strong communication skills with the ability to explain technical concepts to non-technical audiences.
• Organised, proactive, and able to manage multiple tasks effectively.

Desirable

• Postgraduate qualification in relevant field (eg Computer Science, Data Science, Operational Research)
• Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric).
• Familiarity with MLOps practices and version control tools (e.g. Git).
• Experience with deployment and maintenance of ML models in production environments.
• SQL
• MS Excel
• Power BI
• Python and/or R

Behaviours

• Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes