Correlation does not equal causation – just because you see a lot of individuals with a PhD working in data science doesn’t mean you need one.
Before writing this article, I took the time to speak to two
recent PhD graduates – one in Mathematics and another in Cyber Security. Both
are following careers within data science now. Both of the individuals agree
that there is a lot of work within data science that doesn’t actually require
the training a PhD provides.
If you don’t strictly need a PhD to start a career in PhD, why would you do one?
Like with many careers, there are different entry points. Sometimes
four or five years of Higher Education just isn’t enough to quench your academic
thirst. The allure of becoming THE specialist within domain is a noble pursuit.
There are many reasons why you’d choose to take on the challenge of a PhD.
From an employability points of view, the journey to your Viva can often be transformative for the individual, exposing them to new challenges whilst equipping them with many different skills in the process. One of these recent graduates described it like playing a video game with lots of different side missions to the main mission of writing the actual thesis. Often, those ‘side missions’ can bring out new passions or refine skills you never thought you would use.
In a commercial world, these skills allow you to articulate complex problems and solutions to a wide audience. Years of being immersed within research, picking up teaching spots for taught postgrad modules, or setting assessments will allow you to mercurially pick up on what commercial clients may or may not understand in terms of the solution you’re presenting and allow you to adapt your technical delivery to ensure what you’re selling solves your clients problem.
Both individuals have published at top conferences within their field presenting and defending their ideas in front of other specialists within their field. The research itself is of course focussed and as a result in-depth demonstrating the PhD candidate’s ability to think critically and engage with a highly technical and specialised area of research. Many of the solutions you might try or explore will include methodologies your commercial counterparts might be utilising or pioneering. These are all skills that are valuable in an environment where you’re faced with complex problems involving large data sets.
So how can I start a career in data without a PhD?
Last year, I placed more people with Masters level
qualifications into data science roles than those with PhDs. Entry into this
line of work is entirely dependant on what you want to work on.
You could work your way up in a commercial development role, for example as a software developer working with data scientists to develop the commercial offering or tweaking a solution for a customer. Many of these companies promote cross-pollination allowing you to build your own skills and experience within data science including developing / researching the solution. With careful alignment with the specialists you work with and a lot of grit, you could find yourself in the highly sought-after position of having a track record of developing commercial software alongside on the job data science training.
There are many routes into data science that don’t require a PhD. The important factor to ensure is that you regularly get opportunities to apply machine learning solutions to the problems posed by your company’s customers. Your interest, the expertise of your colleagues, and your own research will quickly give you the experience you need to approach a wide range of problems with the right tool.
Whilst there are many great reasons to do a PhD, not having a PhD won’t stop you from pursuing a career in data science. Many of the businesses we work with prefer industry experience or commercial coding experience to several years of study.
My own background is within Higher Education quality assurance and employability. If you’re just finishing your studies now either at Masters or PhD and you’re interested in a data science career, please email him to arrange an opportunity to get acquainted: email@example.com