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Data Scientist – Data & Analytics Products

Job in Glasgow, Glasgow City Area, G1, Scotland, UK
Listing for: Experian Health
Full Time, Part Time position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Machine Learning/ ML Engineer, Data Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 GBP Yearly GBP 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Data Scientist – Data & Analytics Products

  • Full-time
  • Employee Status:
    Regular
  • Role Type:
    Hybrid
  • Department:
    Analytics
  • Schedule:

    Full Time

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at

We're looking for a Data Scientist to join our Data Science team, working on a data and analytics product that supports insurers with property risk and pricing decisions.

This is a hands‑on role with a strong focus on modelling and feature innovation, where you'll develop new predictive capabilities while working with real‑world datasets used in live decisioning environments reporting into our Head of Categorisation. Alongside this, you'll play an important role in maintaining and improving the performance, reliability, and quality of our production data outputs.

While you'll initially focus on an insurance‑focused product, this role will expand over time, offering the opportunity to contribute to new products and data services across other domains such as credit risk and affordability.

What You’ll Do
  • Develop predictive features and models, applying statistical and machine learning techniques to support risk assessment, pricing, and decisioning.
  • Explore and extract insights from structured, unstructured, and geospatial datasets to unlock new data value.
  • Improve existing features and models, identifying opportunities to enhance performance and predictive power.
  • Lead the quality and performance of production data outputs, ensuring accuracy, reliability, and consistency across API and flat‑file delivery.
  • Monitor and improve data pipelines and feature performance, identifying issues and opportunities for automation.
  • Analyse and improve the completeness and integrity of the underlying data estate, driving remediation where needed.
  • Use generative AI tools to improve workflows, accelerate analysis, and enhance product development processes.
  • Work cross‑functionally with product, engineering, and commercial teams to translate data insights into product improvements and innovation.
  • Support client‑facing teams by explaining data behaviour, feature logic, and modelling outputs where needed.
  • Document methodologies, assumptions, and transformations to ensure transparency, reproducibility, and knowledge sharing.
Qualifications and Experience
  • Experience in R (preferred) or Python for data analysis, modelling, and feature development.
  • SQL skills and an understanding of relational databases.
  • Experience working with large datasets, including property, geospatial, or risk‑related data.
  • Understanding of statistical modelling, feature engineering, and machine learning techniques.
  • Experience building and maintaining data pipelines (data cleaning, validation, transformation).
  • Comfortable working with APIs, flat‑file delivery, and version‑controlled codebases (e.g., Git).
  • Familiarity with geospatial data (e.g., spatial joins, shape files, geocoding) and/or cloud environments (AWS/Azure).
  • Commercial experience in a data science or advanced analytics role.
  • Background in insurance, risk, credit, or other regulated / data‑rich industries is advantageous.
  • Analytical mindset.
  • Focus on data quality in production environments.
  • Comfortable balancing innovation (modelling, feature development) with operational ownership (data delivery, pipelines).
Benefits
  • Hybrid working, 2 days a week in our Glasgow office.
  • Great compensation package and discretionary bonus.
  • Core benefits include pension, bupa healthcare, sharesave scheme and more.
  • 25 days annual leave with 8 bank holidays and 3 volunteering days. You can purchase…
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