Happy International Women in Engineering Day!

Here at Bays, we’re committed to supporting our female colleagues and helping them reach their career goals. That’s why we’re so excited about today, where we’ll be recognising our amazing women in engineering and technology, sharing their stories with the world, and celebrating them as an inspiration for other young woman who are interested in pursuing a career in STEM!

Today, we are delighted to share the stories of our amazing data scientist, Holly Jones. Holly has been with Bays Consulting for over 18 months since her graduation. She works closely with a range of different clients, helping them to find the hidden value in their data. We asked Holly what she thinks about a career in STEM.

Tell me about your role in the company and what this involves.

Holly: I am a data scientist at Bays Consulting – this means I deal with a lot of statistics and coding on a daily basis. Working at a small company means I get involved with so many different tasks, so no two days are the same! Some days I’ll spend all day on maths, stats and coding, whereas others, I’ll have back-to-back meetings speaking to clients.

Talk me through what led you to working in this industry. Where did the passion stem from?

Holly: I always enjoyed maths through school, and it was an easy decision for me to choose to study it at university. I went into Uni not really knowing what career it would lead to. I was already at university studying maths, when I’d come across the drama series ‘Bletchley Circle’. Although this is a fictionalised series, it sparked my interest to learn more about the women breaking into ciphers during World War I and made me think about a career in tech and coding.

What would you say is your favourite thing about the role?

Holly: The variety. I do something different every day, some days I could be working on a project about shellfish, and the next day I could be working on a project which helps predict the demand for food banks after COVID. All projects require different knowledge and different statistical approaches, you really do learn something new every day.

How would you define data science?

Holly: A combination of statistics, coding and maths which can be used together to extract information and insights from data.

How is data science an integral part of statistics?

Holly: isn’t it the other way around…

How do “just stats” let us have ridiculous amounts of fun?

Holly: In my opinion, going through university learning maths with statistics can sometimes be very full on. Learning proofs and theorems and having to remember everything for an exam. Working as a data scientist you can apply all of that stats you learnt, and see how it fits in day-to-day life.

What types of projects need statistics?

Holly: More projects than I could ever imagined before I joined Bays. We’ve been using statistics to help us predict the location of where shellfish come from. We’ve also used it in more social good projects – so helping food banks by predicting the demand after COVID to help them prepare. There’s never one route to take when starting these projects, so it involves trying out many statistical approaches and seeing which fits the data the best.

Are data science and statistics the same?

Holly: No. But they often go hand in hand – statistics is the foundation you need to be able to go on to do data science. Statistics is the backbone to a lot of data science algorithms and there’s no use in using them if you don’t understand the statistical assumptions of the model and whether these are the best fit to the data you have.

Why is statistical knowledge important to data science?

Holly: Statistical knowledge is the fundamental step behind most data science algorithms. To perform any sort of predictive analysis or data analysis you need the statistical knowledge behind it.

How do you use statistics on a daily basis?

Holly: I use statistics in every project I do, from analysis the dataset – identifying missing values/outliers, to building predictive models using different statistical methods e.g., linear regression, random forests, Bayesian techniques.

Is data science as fun as it’s made out to be?

Holly: I think so! It all depends on your preferences, but for me, working in a small company with multiple projects on the go at the time, it keeps it interesting. This means you have to constantly research new projects. You can never know it all, it’s such a huge field, but this type of work you are forever learning and trying out new approaches.

How does stats help you tell the story in the data?

Holly: Taking the food bank work as an example, in such uncertain times stats can help give some clarity. No-one could have ever predicted what was going to happen with COVID but through combining multiple datasets and statistics you can start to look back and see patterns and trends in the data which all help in making predicts for the future. The story in the data can be seen through the patterns and trends.

What other skills do data scientists have other than statistics?

Holly: There are so many different roles for data scientists – but working at a small company I have realised how important personal skills are. So, although the technical skills are obviously important like the coding and the stats, the personal skills are just as important. The ability to meet clients and explain to them the insights you find from their data. You might be able to do all the stats and the maths but if you’re not able to explain your findings to them in a clear and helpful way, then they’re not much use for the company at all!

How much machine learning do you use?

Holly: I do use machine learning on a lot of projects, but I think it’s important to note that data science isn’t all about building fancy machine learning projects. A lot of the time does go into finding the data, cleaning the data and getting it into the form you need to go onto building these machine learning models.

Do you enjoy coding?

Holly: I do yes! It’s a good job because I do a lot of it. Coding can be frustrating, and you can spend so much time on one project, not knowing why the code isn’t working, but when it does work it is so satisfying. It can be the simplest thing like missing a bracket that breaks the whole code, but once it’s fixed and it works – it can be the best feeling.

What languages do you code in?

Holly: I code in Python mainly, but R was the language I learnt in. I’ve realised that once you know the basics of coding, it doesn’t really matter what language you choose. It needs a bit of research but switching from one language to another isn’t too difficult from my point of view.

What one piece of advice would you give to someone looking to get into this industry?

Holly: I think the most important thing for me was finding a small company to work at – especially if you are not sure the exact route you want to take. This allows you to try so many different things all at once, I even had a go at some web developing, something I never thought of trying. But that’s an advantage of working in a small company – give you an exposure to so many opportunities.