Case study

Data scientist — Emily Graham

Emily studied physics at The University of Manchester followed by a PhD at the University of Liverpool before she joined THG as a data scientist specialising in machine learning

Why did you decide on this career?

My journey into the technology industry began with my choice to study science A-levels back in school. After starting a career in physics, I wanted to do something that was new to me but still used the skills I'd built over my PhD and data science was a natural next step.

How did you get your job with THG?

When I finished my PhD, I knew I wanted to be a data scientist. However many jobs asked for years of experience, industry-specific knowledge, and/or a Masters in data science. I enrolled onto the THG Accelerator programme, which is a six-month programme that trains STEM graduates for careers in tech, and built up my software skills before starting my current role.

What's a typical day like as a data scientist?

We get to take care of a project from start to finish. The project starts with a research phase, during which I'll be reading papers and understanding more about the data we have to work with. I then move onto the modelling phase, where I use a machine learning model to make predictions based on the data. Finally, we get to show off our software engineering skills by deploying our models into production so that the results can be used by the wider business. As a global technology platform specialising in taking brands direct to consumers, we work on a huge range of projects. Currently, I'm currently working on product recommendations.

What qualities do you think are important for a data scientist?

All data scientists need a good grasp of statistics, maths and coding. These skills are fundamental to understanding machine learning models and applying them to your data. However, no matter how great your work is, you need to communicate effectively. It's rare to come across someone who can easily communicate something highly technical to a non-technical audience; this will set you apart from the crowd.

What part of your job gives you the most satisfaction?

There's nothing more satisfying than when months of work culminates in a finished product that brings real value and it’s so exciting to see your work on a website being used by customers. However, in my job there are small wins every day ‐ from fixing an annoying bug in my code to seeing tiny improvements in the accuracy of my machine learning model.

How can we encourage more women to take up a career in technology?

Studies show that girls' attainment is equal to that of boys, and that they are interested in STEM subjects but lack confidence in them. I think visibility of women working in male‐dominated fields would go a huge way toward fixing this.

In what way is your degree relevant?

Particle physics and e-commerce seem like they couldn’t be more different. But there are a lot of ex-physicists working in data science and there are four of us in my team. My PhD involved a lot of programming, statistics and machine learning - just like my job now. The data might be different, but the techniques used are very similar.

What are your career ambitions?

The next step in my career will be to lead a small team, so I'm starting to work on my management and leadership skills, as well as my technical knowledge. In the long term, I'd like to head up a data science team and gain experience in shaping data strategies. One of the great things about my job is that there are data scientists working in all sorts of different industries and there are many different paths that I could take.

What advice can you give to other aspiring female data scientists?

I've always suffered with a lack of confidence. I felt like I didn't deserve any of my achievements and that I'd soon be 'found out'. Looking back, I can see that I was just as capable as my colleagues. Impostor syndrome is more common in women and it can affect your career in more ways than you might realise. Job adverts, especially in data science, often ask for experience that very few people actually have. My advice would be to get applying, have confidence in your abilities and don't feel pressured to meet 100% of the criteria.

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