Unveiling Data Science Careers: Recruiter’s Insights

Suhruta and Sujoy discussed various aspects of pursuing a career in data science and machine learning. Here are some key takeaways from their conversation.Overall, Sujoy highlighted the importance of practical experience, a strong understanding of the field, and effective communication during the hiring process for data science and AI/ML positions.He also suggested regarding, Online courses and certifications: What’s effiective and what’s not?

Suhruta: Sujoy, I have seen your profile and I could see that inspite of having relevant experience, you have taken several online courses for data science and AI/ML. Earlier you had also mentioned that even now you spend 10–15 hours per week updating yourself on new techniques and technologies. Can you tell us more about the effectiveness of these courses, both from a learning perspective and for professionals who want to get into these careers; for them usability from the perspective of getting a job?

Sujoy: I have done a large number of Coursera and edX courses. Plus, I keep watching YouTube classes. If you want to learn, I don’t think there has been a better time in the history of civilization; you can sit in a room and watch a Stanford and MIT class. That is something I always spend time on. Plus reading research articles, academic papers, etc. are things which we need to do. Online courses are very powerful and critical for me; whatever little I know is due to these online courses.

Suhurta: From a learning perspective these courses are there but for a job seeker, or somebody who wants to break into this career, there are so many courses; how does one pick and choose on what to learn and how does one spend time effectively doing these courses? Can you shed some light on that?

Sujoy: So, this is my personal opinion and not necessarily everybody would agree to this. But just doing an online course and getting a certificate does nothing to your career process, not even an offline course. First of all, you should have a solid understanding of what you’ve learned and secondly, you should also have some experience. This experience should ideally be in a live project because that is the best thing to have. Now, you may or may not get that opportunity in your job. While the project is always the best option, if you do not get that opportunity to get a project, then you can engage in competitions such as Kaggle, hackathons, etc. by which you would be able to prove that you have actually done something. There are so many courses, so many people signed up for these courses, but how would you distinguish between X and Y who have done the same course. Online courses are not very reliable even though these have marking schemes. We will not know the standard of questioning, since as an interviewer I have very little knowledge about all the courses. Of course, if it’s a course from IIM or ISB, etc. there the credibility comes with the institution, but when we look at the number of online courses that are now, it becomes very worrying what those marks mean even if there is a marking system. Therefore you need to combine it with something which is demonstrable which says look I have done this. It need not be a leaderboard but at least if you have a GitHub code and your ability to explain that piece of code or how you think about even a simple linear regression problem is important…(Read More)

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