Driving impact with data – meet one of our data scientists

Want to know what a data scientist does? Meet Louis. He’s part of our Project Athena programme where he uses data science to analyse NHS data and help identify potential fraud. Louis brings experience from across sectors and is committed to building data solutions that make a real difference.

Published: 6 August 2025

Image showing louis the main foucus of the article

How did you get started in data science?

My data science journey began in the insurance sector around six years ago when I started as a data developer and then moved into a data engineer role. I completed a data analyst apprenticeship during which I worked one day a week with a new data science team on a predictive analytics module.

After the apprenticeship, I was offered a role on the company’s first-ever data science project. We built everything from scratch and our model was eventually adopted by underwriters across the business. This experience sparked my passion for building data solutions from the ground up.

I wanted to strengthen my skills so I pursued a degree apprenticeship. I then decided to go deeper so I enrolled in a master’s in computer science and big data analytics at Wrexham University which has opened a world of opportunities.

What types of work have you done across your career?

I’ve worked in both the public and private sector, including the NHS (mental health and ambulance services), telecoms, utilities, finance, insurance, consulting, government, defence and law.

One of the most interesting areas I’ve worked on was identifying fraud involving stolen national insurance numbers in Universal Credit data, especially during the late stages of the COVID-19 pandemic.

What is your role at Project Athena?

I use exploratory data analysis and machine learning to identify anomalies and understand what practices are appropriate. My role is to ask: do we have the right data to investigate this fraud risk?

What’s been a standout moment in your career?

Helping build and train a new data science team while implementing a new cloud platform and data science models from scratch. I loved mentoring others and showing them the value of data science in real operations especially when it leads to real efficiencies and better outcomes. It felt like a full-circle moment: using everything I’d learned, doing the right thing and seeing the impact.

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