4 types of Data Science roles that you should be targeting in 2020! | Ep #11

4 types of Data Science roles

Episode #11 of Data Science & AI Weekly is here! In this episode, Manav will discuss 4 types of Data Science roles that you should be targeting in 2020. Tune in to this episode to listen to Manav talk about the different Data Science roles that you can aim towards in 2020.

TIME-STAMPED SHOW NOTES:

[00:11] Topic of Discussion: 4 types of Data Science roles that you should be targeting in 2020
[00:48] Answering Student Queries
[01:28] Role of a Data Analyst
[03:22] Role of a Data Scientist
[03:51] Junior Data Scientist Vs. Associate Data Scientist
[05:37] Who is a Data Science Consultant?
[07:40] Data Science Industry Specialist
[09:42] ML Engineer, AI Engineer and more
[10:19] Wrap up!
[10:30] Learn more about Data Science at www.insaid.co

Welcome to another episode of Data Science & AI Weekly. My name is Manav.

I’m the Chief Data Science Mentor at INSAID and today we have a fresh, new episode. In today’s episode, I’m going to be discussing with you 4 types of Data Science roles that you should be looking at/ targeting in 2020.

Now if you have not watched the earlier episodes till now, we have done 10 episodes & this is Episode 11 and you should sincerely, I request you to check out those episodes to get you started on your Data Science journey and the link to that playlist is there in the description of this video, just go ahead to the description and check out that playlist.

So today we have an episode which is Episode 11 in which we will be discussing 4 types of Data Science roles to target.

First of all, let me just you know give you a quick brief about why we are doing this podcast so we get a lot of students, I interact with a lot of students and the typical students that we get it in INSAID are working professionals, IT professionals anywhere from 2 years of experience all the way to 30 years of experience and one of the things that these IT professionals usually ask me is that Manav what are the roles for me and when I say me, every IT professional is different, every non-IT professional is different and that’s why it is important to understand the kind of roles available in the job market right now that you should be looking at right.

So, the first kind of roles that are available are roles for Data Analyst. So the first kind of role as Data Analyst now, how is Data Analyst related to Data Scientists? Now the first thing to understand here is that one of the misconceptions that a lot of newbies have is that everybody needs to become a Data Scientist after learning Data Science.

No Data Science is an umbrella term.

Think of it as an ecosystem. So if you want to get into the ecosystem, Data Science, you need to start with, let’s say one thing and that one thing could be Data Analysis. So, when you look at the entire project lifecycle Data Analysis is one part data cleaning is another part Machine Learning is another part.

So as a Data Analyst, what you do is you take care of getting insights out of data, you understand the data, you do a lot of analysis to get fruitful evidences or those insights that will help in decision making, right, but you don’t do any kind of predictive modeling or a little bit of product predictive modeling, but most of your work is related to analysis. So this is the first kind of role. So this will require you to have some basic understanding of data analysis, some basic understanding of Python, some basic understanding of mathematical concepts and some basic understanding of SQL right. So when I say basic, that does not mean that you need to just be basic in all of these fields, you will possibly be a master in one of these areas, but what I essentially mean is that this is the umbrella of keywords or skills that you need for a Data Analyst kind of job. So the first rule is Data Analyst that I’ve just described.

The second kind of role available, and that you should be looking at is the role of a Data Scientist. Yes, you’re correct. If you are looking to get into Data Science, Data Scientist is what you would be wanting to become. Now in Data Scientists, what you need to see is that where do you fit into the hierarchy?

For example, if you’re an IT professional, and you’re looking to target straightaway a Data Scientist role, right, you would need to see let’s say that if you have 2-5 years of experience or 7 years of experience, you should ideally be looking at a Junior Data Scientist kind of role or an Associate Data Scientist kind of role. So if you’re looking at those roles, then the expectations from you in the interviews will also lesson and that becomes an easy entry point for you to get into a Data Science role and in the Data Science world right?

So, Junior Data Scientists, Associate Data Scientists, these are fantastic entry-level Data Science positions after that, you have a Data Scientist role and this role is ideally suitable for someone who has been doing some kind of statistical modeling in their previous job or who has been a Data Analyst in their previous job or even if you have been a regular IT professional you have an understanding of one key area that you think you have a really very, very solid understanding in.

At the same time, you have developed over a period of six months to one year in a Data Science program, you have worked on enough number of high-quality projects to be able to execute real-world Data Science projects, right? So if you have done that kind of work, then a Data Scientist role is great for you.

As I said, this is an end-to-end kind of role wherein you will be doing anywhere from analysis to building predictive modeling to even understanding the business problem to framing a business problem to working on complicated models as well. So, this is an end-to-end typical Data Science role that you undertake when you need to know programming also well and you need to know maths as well.

So, the first role was the role of a Data Analyst. The second role, as I said, is the role of a Data Scientist. Now, this is where comes the third role, and the third role is the role of a Data Science Consultant. Now this role is perfect for those of you who do not want to do a lot of coding in Python and R, this role is perfect for those of you who think that your true strength is in converting business problems into Data Science problems.

Your to strength is in client interaction and Data Science as an approach to clients. And your true strength is adding business value without doing Data Science on a day to day basis. So Data Science consultant is a fantastic role for those of you who are either Project Managers, who are already working as Consultants, who are MBAs, and essentially people who want to look at business problems from a high-level perspective, and then hand over those problems, maybe to hardcore Data Scientists or hardcore Data Science teams for them to do the execution.

So that’s what a Data Science Consultant role is. And these Consultants are also being recruited across verticals and different industries and these consultants are especially companies which are consulting focused companies, for example, McKinsey, or BCG, Bain, you have E&Y, you have Deloitte, you have KPMG, you have PWC and a lot of these companies are building the in-house Data Science capabilities wherein they are looking for consultants who have good understanding of Data Science and can solve Data Science problems for their clients. Right. So, this is a fantastic role and a role that you should be targeting if you don’t want to do a lot of heavy lifting that Data Scientists usually do on a day to day basis. Now, the fourth role, so the first role just to summarize was of a Data Analyst. The second role was of a Data Scientist. The third role was of Data Science consultant and the last role, but a very, very highly paid role and the role possibly which you would be interested in is offered Data Science Industry Specialist. Now, what does this mean? This is a hybrid role, wherein you are a consultant, but you are a consultant in applying Data Science in a particular industry.

Let’s say that you are a Data Science consultant in Healthcare. Now what that means is that you have a little deeper knowledge than that a consultant has in terms of applying Data Science and you can actually build Machine Learning models on your own as well. Unlike a Data Science Consultant who does not do the heavy lifting, but as a Data Science Industry Specialist you do, you are capable of doing heavy lifting, but you do that heavy lifting for a particular industry. And you understand that industry inside out. So think of it as an intersection of Data Scientists and an Industry Expert. And this is a role that I believe every industry needs, every company needs because in the end, what organizations want are Data Scientists who have a keen eye for problems for that particular industry.

For example, the problems faced by the telecom industry are very different from the problems faced by BFSI and the problems faced by retail are very different from the problem faced by Aviation. So what a Data Science industries’ specialist brings is, he brings in that deep industry expertise and knows what are the various verticals, challenges, business challenges that can be solved through Data Science, and actually goes on and solves those problems. Right. So this is the fourth role. And this is a role, which I think a lot of you should be looking at, as I said, it’s an extremely highly paid role, simply because not many people are available in this kind of role because this is very, very niche kind of role.

So these are the four types of Data Science roles that you should be looking for if you are wanting to get into Data Science. Apart from that, there are roles like Machine Learning Engineer, AI Engineer, but I will possibly talk about those roles as well. But since they are towards the engineering side, I would possibly do that in another podcast here.

The goal I had was that from a Data Science perspective, what are the different variations? I have helped you understand those variations in this podcast and I hope that you would have gotten some clarity about where you fit in into one of these four kinds of roles? So this was Episode 11 of Data Science & AI Weekly, I covered the 4 kind of roles that you should be looking for in Data Science. And if you love this episode, just leave your comment in this comment section. Like and Subscribe this podcast, and I look forward to seeing you here another episode. This is one of I’m signing off. Take care!

 

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