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Emma, Digital & Tech, Consumer Health, UK

Emma, Digital & Tech, UK

Emma, Head of Data Science for GSK Consumer Health, explains why an early foundation in STEM subjects can lead to a diverse and exciting career path.

Emma has a Masters Degree in Applied Maths and over the last 12 years has worked in Data Science across a myriad of sectors such as finance, media, and tech.

Why is data science cool?

Data Science is a brand-new technology and a field that’s evolving all the time. We're in a time of frontier science where you might be the first person to use it to solve a problem that you care about. You’re getting the chance to be the first person in all human history to solve a problem using this new technology – and that’s pretty cool.

Did you always want to work in a scientific field?

As I was growing up, I always knew I wanted to work with maths. I've always loved puzzles and problem solving, whether it was brain teasers, riddles or anything like that. For a long time, I thought that meant I wanted to work in finance, so I did dip a toe in that industry, but it wasn’t for me and eventually I found my way to data.

You mentioned exploring a career in finance before data – did you explore any other career paths?

Yes! After university I started working in a media agency, having tried a few roles in finance which didn’t work out. The culture was much more supportive but I missed maths so went back to university. After my master’s I started working at IBM and became a consultant. One of the key reasons I wanted to work there was because they had a female CEO, which was quite unusual for a tech company at the time.

As a consultant I learnt a lot about predictive problems in sectors like the utilities industry. From there I went to a tech start-up, working in data science. I loved it and became Head of Data Science. It was fast paced with many challenges but working for a company with an amazing female CEO, where it was so focused on female empowerment, was an awesome experience. I then followed my mentor - an amazing woman in data, Caroline Warboys – to another start-up and built the team up from scratch there. At which point I was approached with the opportunity to come and do the same at GSK Consumer Healthcare.

Let's unpick your role in data science a bit – what is it?

Data science is the field of studying data - that's everything from analysing data and understanding patterns, all the way through to dealing with data at scale using statistics and computer science to create predictive, descriptive and prescriptive models. These models often simulate the future or use AI to identify optimal outcomes of a complexity that just hasn't been possible at any time in history before.

Applying it to GSK Consumer Healthcare means a lot of variety as we work across all aspect of the organisation. It might be in our supply chain; using AI to optimise our logistics and manufacturing to improve our sustainability and efficiency. Or for R&D; how can we use AI to be more predictive on our formulations or consider what are the ethical implications for AI in consumer healthcare?

We get to work with amazing people at GSK, in the data science team we combine the vast amount of deep domain expertise from our colleagues with cutting edge data science to create solutions.

There is nowhere else in the world where you can use data science in AI to help everyday healthcare at this scale, it's a unique opportunity doing it at GSK Consumer Healthcare.

Do you have to be amazing at maths to go into data science?

In its short history data science has been quite dominated by stem subjects: computer science, physics, maths etc. However, what's amazing about the field as it’s evolving, and GSK, is we're thinking of different routes to bring people in. We're on our second year of data analytics apprenticeships and we have people joining who are school leavers who don't necessarily have a really deep background in maths but who want to learn about problem solving and are interested in technology and how you apply it.

Science has been a traditionally male-dominated field – do you see this changing?

The Turing Institute released a report last year looking at diversity and gender diversity in data science in the UK. The report showed that around 18% of AI publishers or practitioners are female, which is low even by STEM standards. It’s definitely an area where we need more women coming in but unfortunately it looks like the numbers are going down – not up so we need to think about how to drive change.

To work in this industry, you need to be able to think critically, empathetically, consider lots of different variables at once and be curious, and women have amazing skills in all these areas. AI is the most exciting and innovative tool we have to solve problems. I would hate to think that women are missing out on being able to use this epic tool and be part of this wave of innovation - it’s an incredible career opportunity!