Careers

NGC Career Talks Series – Career Hack: Journey of a Neuroscientist to become Data Scientist

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What is Data Science? “Data Science is just a fancy term indicating work with lots of data” said Dr. Gautam Kumar Pramanik at the beginning of his talk, during which he led us through a journey towards his current job at Savedriod AG. This startup based in Frankfurt deals with, among other things, financial and crypto data analysis, fraud detection, text mining and Blockchain. But how did he go from Neuroscience to Data Science?

Gautam moved from India to Germany, to do a PhD at the University Medical Center in Mainz. His work on two-photon imaging of cortical neuronal activity in a multiple sclerosis mouse model led to a publication in Nature Neuroscience. About half a year before the end of his doctoral studies, he started thinking about his future: to remain in academic research or to leave? After careful deliberation, he realised he wanted to leave academia. The fierce competition for grants and tenured track positions as well as the amount of administrative work group leaders face are among the reasons that prompted him to pursue a non-academic career path.

But what to do instead of a Postdoc? Gautam started exploring many career opportunities, from consulting to the funding of a startup, from regulatory jobs, to publishing. He failed at nailing any of them, including biotech and pharma job interviews, because his skillset apparently wasn’t attractive enough. Then, one day, he attended a talk on machine learning given by Prof. Dr. Helmstaedter, head of the Connectomics Department of the Max Planck Institute for Brain Research. Listening to his presentation, Gautam understood that you need programming skills for the kind of data analysis Helmstaedter was showing and he decided to learn how to programme. At first, he figured he was not feeling comfortable with programming, but forced himself not to be scared of acquiring new skills and soon started to enjoy it.

Gautam's journey from Neuroscience to Data Science was not a straight one; it implied instead several steps of career-analysis and skills improvement. (NGC/Design)

Gautam’s “smooth start” began with online courses, Youtube tutorials and bootcamps. He also brushed up his statistics and tried to understand the math behind statistical algorithms. Then, he started playing around with tools such as Tableau and R-studio (or, simply, R). His first attempts at data analysis were made on his own bank transactions after downloading them from his online banking. Another important element in his career development was networking: he attended Artificial Intelligence- (AI) meetups and other events where he could meet Data Scientists and AI specialists. It is at one of these events that he met his future boss. This encounter led to a freelancing job, which eventually developed into a full-time contract!

Before embarking on a journey towards a career in Data Science, as Gautam did, make sure you are really interested in it and you feel confident enough to change your career path. As our speaker told us :”avoid following social conformism and get outside of your comfort zone”, beginning with keeping away from common statistical software which do not allow for developing the skills required for Data Science. Make a study plan with a reliable timeline; it is better to start taking up Data Science tools (Python, R, Kaggle, Tablau, MySQL to name some) and practicing around for six months before the end of your PhD. In order to deal with the kind of data you are given in Data Science tasks, you will need good analytical and problem-solving skills. When you finally prepare your CV for job applications, be honest about your skills as you will be tested during the interview process, typically by being assigned a big set of data to analyse.

Above all, don’t despair: industry is hungry for Data Scientists!

Written by Chiara Galante; Edited by Fazi Bekbulat. Featured Image: Courtesy of Gautam Kumar Pramanik. Info-graphic: NGC/Design.

Dr. Gautam Kumar Pramanik is co-organiser of monthly AI-Meetups in Frankfurt, where prospective Data Scientists can meet professionals, discuss about tools and learn new ways through data analysis. For more information: https://www.meetup.com/de-DE/Artificial-Intelligence-Meetup-Frankfurt/

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