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    You are at:Home»Graduate Careers»Choosing Your Career»Is University the Only Path to Becoming a Data Scientist?
    Is University the Only Path to Becoming a Data Scientist?

    Is University the Only Path to Becoming a Data Scientist?

    0
    By CareerExperts on 18th September 2018 Choosing Your Career, Graduate Careers

    Despite the constant fluctuation in tuition fees, university continues to be the most direct route to a skilled career. However, with more and more people gaining university level qualifications than ever before, is the value of a degree diminishing? And if so, are there any alternative routes to becoming a data scientist that offer equal value, without the expense?

    We spoke to Geoff Cunningham, a Data Science Manager at fleet tracking company, Masternaut about the various career paths into this lucrative business.

    Can you tell us a bit about your own educational background?

    Like most young people, I didn’t really know what career route I wanted to peruse, or what I wanted to study. So, when it came to choosing my A-Level’s I just went with the subjects I enjoyed and that I did well in – for me, it was Maths, Physics and Chemistry. For university, I initially wanted to study Natural Sciences at Cambridge, however, I didn’t get a place on the course. Whilst this was disappointing at the time, in retrospect it was for the best.

    Following my rejection from Cambridge, I decided to take a gap year to gain some work experience. I secured an admin job at TWI, a welding institute and research company which really opened my eyes to a wide range of career possibilities. I took a keen interest in the technology they were using and gradually gained more exposure to these projects. This experience resulted in me changing my degree discipline to engineering, a subject I had become increasingly passionate and interested in. I reapplied to Cambridge and completed my degree in Aeronautical engineering.

    How relevant was your degree to your current role as a Data Scientist?

    When I was at university and even after I graduated, Data Science was totally off the map for me. It wasn’t a career path I’d ever thought to pursue, or had even heard of, as it wasn’t really present in my educational background. Whilst I have always been interested in programming, having dabbled in it as a hobby in my spare time, it was never really a contender career-wise. It’s actually surprising how many people pursue careers that are not directly relevant to their degree subjects!

    Do you think your degree was necessary to get to your current position?  

    I have questioned the value of what I learned at university in the past. I spent two years learning the fundamentals of engineering and a further two years specialising in my niche and if I’m totally honest, I don’t think I’ve applied any of this knowledge in a professional context. So, was there any value to the time and money I spent at uni? I still think so. University is about showing your commitment and showing that you can learn. It’s about gaining ground-level knowledge that lays the right foundations for you to build your career upon. Whilst there are many other routes people can go down these days, in my experience these learning opportunities tend to lack that basic level stuff.

    What are these alternative routes?  

    As a relatively new field, Data Science is very accessible and there are lots of opportunities for online learning. In some fields online courses are undervalued, however data science is one of the few industries that shows respect for ‘self-learning’. Especially because, up until very recently, there has never been a specific ‘data science’ degree. Most people working in the industry come from a range of STEM subjects, which makes the industry very broad.

    What do you look for when recruiting a new Data Scientist?

    When interviewing someone for a Data Science role the first thing I look for is passion. Passion yields innovation and that’s very important in a data-driven industry. Secondly, I look for fundamental knowledge. I’ll usually explain a real-world problem to the candidate to see how they would approach the project. Here, I’m looking for that basic understanding and core knowledge, not the most technically advanced solution. You should only build in complexity when its necessary to improve your results, not before, and you should never start with a complex solution. Finally, I want to know how they see the future of the industry and its potential limitations. Having a strong opinion about something like the future of an industry is a key way to evaluate someone’s passion for it and to find out what drives them. Personally, I’m driven by exploring data solutions that will spark real-world improvements.

    Finally, what advice would you give to a school leaver who might be interested in Data Science as a career opportunity?

    I’d advise any school leaver to take a gap year. Whether it’s to pursue a formal work arrangement for a year, to get some interning experience, or even to travel. A singular academic experience doesn’t allow you to grow, learn about different options, or apply things from a different perspective. Getting a different experience is so valuable before you commit to one career path.

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