Hi, I am starting to apply for the position of a data scientist in Europe (Germany, The Netherlands, etc.) and I need some advice. Recently, I finished my PhD in experimental condensed matter physics. On searching for possible opportunities outside academia, out of several options I found, data science seems very interesting to me. The main reason why it seems interesting to me is because of a small phase during my PhD research - after completing my experiments when I was analyzing the data from my experiments, I developed algorithms and wrote programs in MATLAB and I enjoyed this phase a lot. And because of this I think this field seems very interesting to me. Currently, I do not have any experience with professional data science, but I am learning the basic tools of data science and machine learning from online courses on Coursera. I am very good with probability, statistics and analytical thinking. On searching online, I got the feeling that first I need to do an internship in some company before finding a real data science job. How true is this? Is internship necessary even after a PhD? The kind of job that I want is of data analytics rather than data engineer. I am interested more in the analysis of outcomes of the data, understanding what it means and make models. I do not want to be the one digging and plotting data, which would involve a lot of programming like an IT guy. I understand that I will need to do some programming irrespective of my position and I am okay with that. So, how can I look for this position which suits my interests most? I will be grateful for your advice, thanks a lot.
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I was very recently in your same shoes: applying to data science and data analytics positions in Germany/Netherlands. Don't have a PhD/ Ms though. I actually used MATLAB for my BA grad project couple of years ago, but you have to know that that's really not the language used in industry though. Learn Python or R, I recommend Python. Take courses that help you build a Github portfolio. I had 5 projects covering different topics e.g. Regression, classification, image classification, market segmentation, Flask deployed, etc. This will get you familiar with the basic DS pipeline i.e. retrieve data, EDA, preprocessing, baseline model, selected model, tuning params. After that apply to as many companies as you can or get a referral if possible. I sent out 100 applications and got 2 job offers in the end. Good luck!
Hi, Thanks so much for your reply. Can you please tell me which online courses did you followed? And how did you found out the projects to work upon?