At a Glance
- Tasks: Develop predictive models and insights using data to support insurance risk and pricing decisions.
- Company: Join Experian, a global leader in data and technology with a people-first culture.
- Benefits: Enjoy hybrid working, competitive pay, generous leave, and wellness initiatives.
- Other info: Be part of an award-winning workplace that values diversity and innovation.
- Why this job: Make a real impact by innovating with data in a dynamic, collaborative environment.
- Qualifications: Experience in R or Python, SQL skills, and a passion for data science.
The predicted salary is between 50000 - 65000 £ per year.
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.
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, shapefiles, 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 additional annual leave.
- We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering… the list goes on.
- Experian's people first approach is award‑winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few.
Experian is proud to be an Equal Opportunity and affirmative action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Data Scientist – Data & Analytics Products in Glasgow employer: Experian Health
Experian is an exceptional employer that prioritises employee well-being and professional growth, offering a hybrid working model in the vibrant city of Glasgow. With a strong focus on diversity, equity, and inclusion, employees benefit from a comprehensive compensation package, generous leave policies, and numerous opportunities for development within a collaborative and innovative work culture. Recognised as one of the World's Best Workplaces™, Experian fosters an environment where every individual can thrive and contribute to meaningful projects that impact lives globally.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist – Data & Analytics Products in Glasgow
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Experian. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving predictive modelling or machine learning. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your R or Python skills. Practice coding challenges and be ready to explain your thought process. Remember, they want to see how you approach problem-solving!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Experian team!
We think you need these skills to ace Data Scientist – Data & Analytics Products in Glasgow
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with R or Python, SQL skills, and any relevant projects that showcase your data analysis and modelling abilities. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Mention specific experiences that relate to the job description, especially around predictive modelling and data pipelines.
Showcase Your Projects:If you've worked on any interesting data projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing real-world applications of your skills, especially in insurance or risk-related areas.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Experian Health
✨Know Your Data Tools
Make sure you're well-versed in R or Python, as these are crucial for the role. Brush up on your SQL skills too, since you'll be working with large datasets and relational databases. Being able to discuss your experience with these tools confidently will show that you're ready to hit the ground running.
✨Showcase Your Analytical Mindset
Prepare to discuss specific examples where you've applied statistical modelling or machine learning techniques. Think about how you’ve developed predictive features or improved existing models. This will demonstrate your analytical skills and your ability to contribute to the team’s goals.
✨Understand the Business Context
Familiarise yourself with the insurance industry and how data impacts risk assessment and pricing decisions. Being able to connect your technical skills to real-world applications will impress the interviewers and show that you understand the bigger picture.
✨Prepare for Cross-Functional Collaboration
Since this role involves working with product, engineering, and commercial teams, think of examples where you've successfully collaborated across different functions. Highlight your communication skills and how you can translate complex data insights into actionable improvements for products.
