"Keep Learning" - Reuben Sodhi, Data Scientist at Frame

Hi Reuben! Thanks for speaking with us. Tell us about yourself - what's your background and how have you progressed your career?

I’m currently working as a Data Scientist for Frame, a Data Science and Machine Learning consulting start-up based just outside of Huddersfield. We help clients solve problems using Data Science and develop our own E-commerce based products. I’ve been working here for roughly a year and a half and in that time I’ve gained some amazing experience in the Data Science industry working as part of a small but solid team of eight people. This is my first full-time job and previous to this role I completed an internship and work experience placements in the Finance industry. As for my academic education, I have a BSc in Mathematics and an MSc in Data Science and Analytics. I began this role as a Junior Data Scientist with a good analytical foundation but little to no understanding of how Data Science is used in business. By working on projects at Frame I have attained an understanding of the field on a commercial level and how Data Science techniques are leveraged on a production scale.

What drew you to a career as a Data Scientist?

I have to admit that my career in Data Science wasn’t completely planned. After I completed my undergraduate degree my plan was to start looking for jobs in the Finance industry. However, this also happened to be the time when the Covid pandemic hit so I decided to continue studying and apply for a Master’s degree. After some research, I came across the field of Data Science and Machine Learning. The first thing that really struck me was how many industries this field spans across, from Finance and Big Tech all the way to Healthcare and Retail. For me, this really indicated that Data Science is a vital and in-demand profession that has wide applicability to different business sectors. But what really sealed the deal for me was researching what a career in Data Science entails. I was really drawn to the concept of being someone with a wide range of tools under their belt, such as machine learning or mathematical modelling, and having to figure out which tool best suits the problem at hand.

What excites you about your industry, now and in the future?

There are many things that excite me about the Data Science industry but something that never fails to amaze me is the speed of innovation in this industry. It seems like almost every week I read about a new innovation made using Data Science or Machine Learning that solves a problem previously thought to be incredibly challenging. A very topical example of this is ChatGPT which is already beginning to make incredibly advanced search tools used previously, such as Google, look obsolete. This rapid innovation also has some very encouraging consequences going into the future. Data Science and Machine Learning are being used already to solve some of the major issues facing the world. Some examples include using computer vision to improve automated recycling efficiency rates and hence reduce plastic pollution, and also using machine learning to automate the drug research and discovery process which will increase the turnover rate of life-changing therapeutic drugs. In this sense, it is very exciting to be a part of an industry that has the potential to make positive contributions to the world.