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