A guide to ‘doing data’: What it’s like to be a data scientist

Hannah Green, 30, is a lead data scientist for BAE Systems working as the data platform lead on a project with the Royal Navy.

Photo by Christina @ wocintechchat.com/ Unsplash

When I set out on my career I went into cyber security and specifically data.

I started out handling alerts for what was our Managed Security Service. This is when software flags up when it thinks there might be a malware intrusion on a network and you have to investigate to determine if it is a threat, its seriousness and what action needs to be taken. I did that for nine months, then moved into writing the algorithms that tell the computer how to detect those threats.

The job was very much about keeping networks safe and was usually on behalf of commercial clients – so think banks, pharmaceuticals and big energy companies. The vast majority of people wouldn’t be aware of what we do unless you work for one of those companies, but it’s all about keeping intellectual property and knowledge safe.

Becoming a data scientist

That is when I became a data scientist. According to that slightly questionable source of knowledge, data science is ‘an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data.’ I would say this is actually pretty spot-on.  The insight generated often leads to the creation of new algorithms, and can ultimately lead to artificial intelligence.

Read more: Why thought diversity and disruption is so important in tech


Once I understood the world of data and the jobs available in it, personal motivations drew me to data science as a career choice – over, for example, data engineering. My code just has to work – engineers need to write beautiful, fully supportable, long-lasting code. Data scientists, by contrast, are chasing the value in the data – productionising that value for long-lasting impact can be an entirely different skillset and if I’m honest, I don’t always have the patience for it.

Working in defence

After six years in cyber, I jumped into defence. Whereas my cyber work was product and service focused, with some customer interaction, defence is very much consultancy-led.  Despite having joined a consultancy deliberately to give myself different opportunities, this would be the first time I was truly ‘consulting’.

Consulting is all about helping clients solve their problems. We go to their offices and help them in whatever way they need – whether that be filling a role for a few weeks while they hire someone, or bringing our expertise and experience to help them build a whole new capability over the course of several years.

Data scientist
Photo by Christina unsplash.com/@wocintechchat

Right now I’m building a data platform for the Royal Navy to enable the Navy to better exploit its data. So although once again, nobody really sees the platform itself, it allows other people to build applications on top – much like apps that run on Android or iOS. The range of things those apps will help with is huge. There are apps for planning fuel usage, medical use cases, automated manuals, predictive maintenance. It’s really wide-ranging.

I like to see the difference my work makes. In the Royal Navy, 80 per cent of my end-users are 18 to 30, and most of the technology has been left behind a little. Now we’re upgrading the technology – it’s making people’s work lives just as technically-enabled as their home lives are, and hopefully better for it.

It’s been really inspiring to be involved in defence. There is so much that isn’t always seen. I didn’t realise how much of what the Navy does is humanitarian work until I was in amongst it all. For example, it’s the Navy engineers who go and help rebuild communities after devastating hurricanes in the Caribbean. It makes you feel like you’re really making a difference.

What to study at university

For data science what you need is a maths background, engineering, physics, software – basically anything that teaches you how to examine data and take an evidence-based approach to problem-solving.

A lot of degree courses now will involve data. Take as many data modules as you can, especially ones that are working with real data, solving real problems.

The other component of being a consultancy is that this side of things is very people and communication focused. It’s knowing how to determine what someone actually wants, how to share that with others while also maintaining a strong delivery focus. A lot of that is learnt on the job – and because of this, it is an industry that is very self-driven. Knowing what you want to get out of it is important and can help you identify which opportunities you need to really grab. You also need to be able to identify where you can improve, what skills you want to develop, and know when to ask for help.  These are all ‘softer’ skills that you can be working on developing while you are studying.

Even within consulting there are options – you can stay very technical and become what we call an ‘SME’ – a subject matter expert – or you can be more of an all-rounder.  In the latter you spend the first few years building up your skills, then you start learning your people management and business development. There is always something new to learn!

Choose the right degree for you

I did a general engineering degree as you can do a lot with it. I didn’t know specifically what I wanted to do at the time, I was quite interested in energy production and renewable energy sources but it was broad enough that I could do a lot of things. I wanted to do a degree that would put me directly into a job but I wanted that job to have flexibility. I can have a very short attention span, so I accounted for that.

My degree changes every year depending on what the market wants. And the year I went they added a whole load of programming and data that hadn’t been there before. I realised the thing I really enjoyed is getting value out of data. I like programming to get results, not programming for the sake of it. That’s when I decided to ‘do data’.

The big one with A-Levels is maths. Maths is so important. Degree-wise you can do a wide range of subjects as long as you’ve got the fundamentals of maths and programming there.  And you don’t actually have to study programming – that is something you can learn through courses or self-study, but I would definitely recommend getting a grounding. And communication! Practice speaking, presentations, take all the opportunities you can no matter how scary they are at the time.

Get work experience

I highly recommend trying to get an internship while you’re at Uni. It’s so much easier getting through your final year knowing you’ve got a job to go to, and most internships will hire you afterwards if you do well.

As an industry, we’re quite bad at actively providing work experience, but that doesn’t mean that we won’t. It just means that we don’t run the big schemes. We will, however, make the effort to do it, it’s just a bit harder because of security clearances and stuff like that.

One last thought

If you like to fix things and you want the flexibility there’s genuinely nothing better. If you’re going to do it, do it for the right reasons, and the right reasons have to be yours. But don’t not do something because you haven’t seen anybody else do it. There’s always a first – and that could be you!


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