Tune in to Episode #13 of Data Science & AI Weekly! In this episode, Manav talks about the top companies that are hiring for different Data Science Roles.
TIME-STAMPED SHOW NOTES:
[00:13] Topic of Discussion: Which companies are recruiting for Data Science roles?
[00:37] Big product companies and Data Scientists
[02:04] Data Scientists getting hired by IT Services companies
[03:47] Future of Data Scientists in non-tech companies
[04:48] Data Scientists in Start-ups
[07:27] Wrap up!
[08:00] Learn more about Data Science at www.accredian.co
You can follow the podcast here.
Welcome to Data Science and AI Weekly. This is Episode 13 of this amazing podcast series that we have been doing. My name is Manav, the Chief Data Science Mentor at Accredian. And in Episode 13, we have a super interesting topic that a lot of you have been asking for long, which companies are hiring for Data Scientists and what kind of roles are available? Right? And what’s the difference between the various companies which are hiring for Data Science roles. So there are essentially four kinds of companies that are currently recruiting for Data Scientists out there.
The first kind of companies are your big product companies. These are companies like Microsoft, the usual big tech product companies like Microsoft, Google, Facebook, Amazon. So these are companies which understand Data Science really well, which have been the frontrunners in this space, and which are essentially looking for the top notch talent in the space and They pay really well, they have very well established Data Science practices. And you as a Data Scientist, you would enjoy working in these companies not only because of the brand, but because of the kind of work that you will be doing. So the first category is what I call big tech product companies. Right. So that’s the first kind of companies that are recruiting for Data Scientists. tracking the Data Science roles in these companies is usually requires you to not be only good in your core Data Science skills, but these companies will also test you really, really deeply with your problem solving skills. So it is not only if you’re applying for a Data Science tool you’re going to be interviewed on Machine Learning, but a lot of the interviews will be focused on problem solving, how do you solve a problem? How do you look at breaking down a problem it can be also some basic computer science related data structure related questions as well. So depending on the company that you are applying for, depending on the role in interviews would also differ. So, this was the first type of companies big product tech companies. The second kind of companies is where a lot of openings also are in India specifically, these are your IT services companies, all of the IT services companies big IT services companies, which employ lakhs of people like TCS Infosys, Wipro, FCL, Capgemini. All of these companies are looking to build something that you must be aware about if you’re hearing if you work in one of these companies, which is digital practices, they are moving towards serving client on digital platforms, and Data Science and Machine Learning is one of the key part of strategies for these companies. So what you would want to do if you’re looking to grab these companies is that if you come from one of these companies itself transitioning for you into a Data Science roles in these companies would be much, much much easier. In fact, I would highly recommend you to do that because transitioning internally is usually the easiest thing to do. So if you’re working in Infosys, and you’re working and testing, and Infosys currently has Data Science openings, and if you think that you’re capable enough and you have some connections and then internally trust me, transitioning is much, much easier than what you might think it requires some bit of connection, some bit of networking, and obviously some bit of Data Science of good Data Science skills as well that That goes without saying. So, this is the second type of companies which are your IT services companies. Now, the third kind of companies is a companies which possibly we do not associate Data Science with, but are also recruiting for a lot of Data Scientists. These are what we call non tech companies. These are your banks like JP Morgan Wells Fargo, icse, a bank, Citibank, these are your retail firms. These are your oil and gas companies. These are your abs Companies These are your fmcg companies. So every industry, healthcare farmer, every industry that you can think of right now is looking for Data Scientists. And if you belong to one of these companies, trust me transitioning internally is usually the easiest thing to do and transitioning in this same industry in vertical also is easy to do. So, this is the third kind of companies here, the requirement is not as much as the first kind of companies, big tech product companies that I spoke about, but it is reasonably good skills, you need to have almost at par with what is required in IT services and sometimes maybe a little more. So this is the third kind of companies which are currently recruiting which is non tech companies. The fourth kind of companies are your startups.
Given the fact that today India is hub to a lot of lot of very, very fast growing startups which are making amazing impact on the country and for doing amazing work for their users. Startups right now are recruiting for Data Scientists, but the tiny startups that you would ideally want to target who should be startups, which are at least which have 500 or 200 plus employees, because if you’re looking at entering a startup at a little less than that size, they might not have predefined Data Science problems or they might not even require Data Science at that level. So you can apply essentially what I say is you can apply Data Science only when there is certain amount of data that you have. So at a level of 200 people or 100 people company usually has some historical data company usually have some sense of whether they need you for what kind of job they would want you to accomplish. And this is another fantastic role for those of those of you who hate working in big established bureaucratic multinational companies. Who would want to grow fast with a startup which is growing like a rocket ship. But here, you as I said, you need to be more flexible because a lot of times the problem statements might not be clear a lot of times you might be the first Data Science that the company is hiring, and the company might itself not be clear, very clear, it might be part partially clear but might not be might not have a very long term view of what Data Science can do for you. So it’s fantastic for you, if you are a person who can lead who can show the way who can deliver ROI and who can essentially show the startup that if they have to go from 200 to 505 hundred to 1000 people how what what all ways can you help them at various stages, whether it in terms of inventory management, revenue management, operations, people and a lot of other areas as well. So that is the fourth category which is the startups so these are the four big categories, depending on Where you currently working and depending on where you want to target you, and depending on where you think is achievable, you would want to start with the lowest hanging fruit. What I always recommend student is don’t go for the most difficult positions because they will not come easily go for the lowest hanging fruit, grind those roles, first get into Data Science for one or two years, then think about the next transition that you would want to do. So this was Episode 13 of Data Science and AI weekly. My goal here was to help you see which companies are recruiting for Data Science scientists right now. And I hope that now you would have more clarity about the segments of companies. I hope you love this episode. If you did, just leave a comment in the comment section. And if you want me to cover a particular topic that you think that I should be covering, leave a comment in the chat window.
I will definitely try to pick up our topic soon. So this is Manav of Accredian and I look forward to seeing you tune in to another episode. Thank you for tuning in to this episode of Data Science & AI Weekly I’m signing off now.
