Why bioinformaticians should consider themselves data scientists

Phil Chapman

2018/03/03

My background

I’ve been a bioinformatician for most of the 20 years since I graduated, but now I’m a data scientist working for the Civil Service. In this post I’m going to explain why I made this change, and why I think all bioinformaticians should think of themselves as data scientists with a specialism in biology, rather than as a biologist with a specialism in computational science.

I started my career at AstraZeneca working in a genetics and sequencing lab, looking for variations in genes that might explain differential response to drugs. I soon realised that I’d rather be analysing data than generating it, and was able to transition to a bioinformatics role in the company. I ended up being responsible for bioinformatics support to drug discovery projects in the company’s diabetes and obesity group, and then left and joined Cancer Research UK where I did a very similar job supporting oncology projects.

Issues

Whilst I loved what I did, there were issues:

Becoming a data scientist

When my group leader at CRUK retired, I decided that I should give data science a go. I could see that many of my skills in consultation, stakeholder engagement, project planning, coding and statistics would be transferrable. To my surprised I got the first job I applied for and started in November 2017.

What have I discovered? Well for a start the definition of a data scientist is just as varied as that of a bioinformatician! I was concerned that my lack of formal statistical training might be a problem, but I’ve not found that to be the case. Perhaps if you want to be a deep learning specialst at Google you need that specific background, but mostly companies are literally crying out for people who can not only write code and do analysis, but also work independently, develop an understanding of the business, and communicate with non-technical people. As a bioinformatician you will definitely have something to offer! In fact, bioinformatics experience is quite sought after in data science.

What’s great about being a data scientist?

The thing I like the most about my job is working in a team and in a community of data scientists, and being focussed on projects with practical benefit. Doing the computational stuff well is important, other people in the organisation are really interested in what you do, and want to develop data science skills themselves. But most of all it’s the universe of opportunity that opens up - since I changed my LinkedIn job title to ‘Data Scientist’ I get 4 or 5 messages a week from recruiters. It’s a really competitive job market, and you’re in demand. There is a clear career progression from Data Scientist, to Senior Data Scientist, to Lead Data Scientist, to Head of Data Science, and this doesn’t have to be in the same organisation. Apart from a very few biotech and pharmaceutical companies, those sorts of opportunities just don’t exist in bioinformatics.

As a Data Scientist, there are opportunities in almost every sector you can imagine, from energy, to finance, retail and so on. Whilst I would love to work in healthcare again eventually, for now I’m quite content to learn my trade in other sectors, knowing that I can bring that experience back at some point in the future.

So if you’re a bioinformatician and wondering where to go next, there might be more opportunities out there than you think if you think of yourself as a data scientist!