Tune into this Episode #2 to find out who is Data Scientist and what are the top skills you need to learn to become a Data Scientist. The podcast is hosted by Manav, one of the Top 20 Data Science Academicians in India.
TIME-STAMPED SHOW NOTES:
- [00:10] Topic of Discussion: Who is a Data Scientist? What do Data Scientists do? Skill-set and qualifications of a Data Scientist.
- [00:36] Recap of Episode #1.
- [00:57] Qualifications needed to become a Data Scientist.
- [01:22] 3 skills needed to become a Data Scientist.
- [01:50] Dr. Kirk Borne at INSAID
- [02:42] What Data Science skills are organizations hiring for?
- [03:50] Different Data Science Roles and how to get them?
- [05:00] What is industry-specific Data Science experience?
- [06:09] Wrap up!
- [06:20] Learn more about Data Science at www.insaid.co
You can follow the podcast here:
Hi, Welcome to another episode of Data Science & AI Weekly. I’m your host for this podcast. My name is Manav and what I’m going to be covering today is who is a Data Scientist, and essentially, what are the skill-sets that you need to become a Data Scientist, what do Data Scientists do and are there any qualifications, are there any certifications or is there any experience criteria that companies use to select the right Data Scientists?
We will answer all of these questions. And just to recap what we did in Episode 1, what we covered is we covered the journey of Data Science and why Data Science has become such a hype and we also looked at what does the Data Scientists exactly do.
But what we want to do in this episode is that whether you can become a Data Scientist and let’s start that by first of all looking at what qualifications are required to become a Data Scientist. Now what you will be surprised by is that there is no specific qualification you’re required to have to become a Data Scientist. You don’t need to do an MS in Data Science, you don’t need to do any particular program, anyone from any background can become a Data Scientist.
If you master three specific skills, these skills are A) Computer Science B) Statistics, and C) Domain Expertise. If you master these 3 skills, anyone, even if you are an aerospace engineer, can become a Data Scientist. Let me give you an example.
In 2019, we had the world’s No. 1 Data Science Influencer Dr. Kirk Borne at INSAID.
He is a Principal Data Scientist at one of the top consulting firms called Booz Allen Hamilton, what you’d be surprised that he’s in his 50s or 60s and that he was earlier working with NASA. He had nothing to do with Data Science and he advises top companies on their Data Science practices.
So as long as your fundamentals are strong, and as long as you are focusing on these three areas, that is becoming good in a little bit of programming, a little bit of statistics & math and the understanding of how this is supposed to be used in a particular industry, you can become a Data Scientist. Now the question is that what specific skills and experience organizations are looking for in potential Data Science recruits.
Now that’s an important question, right? The answer is that any company when they’re looking for recruiting Data Scientists, first of all, look at what the particular role is. For example, there are roles like Data Scientists, Junior Data Scientists, Senior Data Scientists, Principal Data Scientists & Chief Data Scientist. So, this is the entire hierarchy of roles. Now, for example, if an organization is hiring for a Senior Data Scientist, then the organization expects that you should have worked as a Data Scientist, should have a couple of years experience and then you would be considered for a senior Data Scientist’s role.
But let’s say that an organization is wanting to have entry-level Data Scientists which are also called in some cases, Junior Data Scientists, who to a large extent, do the work of a data analyst. So you are expected to just have the skills of a data analyst, right? You don’t necessarily need to have a couple of years of experience. If you have experience as a data analyst, well and good, but if your fundamentals are good and you have done a rigorous Data Science program that should be a good enough starting point. So essentially, just to summarize from an experience perspective, what organizations are looking at is whether for that particular Data Science role and as I said there are different Data Science roles, contrary to what a lot of newbies starting in this field, believe, organizations are recruiting for all kinds of positions in Data Science, you need to see which is the right position for you, it can be a junior Data Scientist or a Data Scientist. If you are coming from a Data Science field, then you could look for a senior Data Science role, or a Head of Data Science role as well.
Now, what is also important is you need to look at the industry that is hiring you for a Data Science role. For example, let’s say that you’re interviewing for a Data Science role at Novartis or a healthcare company, then if you have a background in healthcare, then that certainly helps you a lot as compared to you going to Novartis and you having an experience in an industry which is not very relevant to healthcare. So a lot of companies want sector-specific or industry-specific experience so that you can get started immediately.
Let’s say that you are recruiting for a Data Science role in Vodafone or a telecom company. So, if you have some background in telecom that certainly helps quite a bit. Again, this is not a generalization, there might be industries, which are not looking for experience in their particular industry, which are happy with generic Data Scientists.
But if you have that particular industry’s experience that certainly helps. So, that was a snapshot of the kind of qualification that you require, the kind of experience that you require, and the kind of additional skill-set that if you have certainly helps you getting Data Science roles and will help you become a Data Scientist.
So, this was Episode 2 of Data Science and AI Weekly. What we covered in today’s episode is who can become a Data Scientist. If you liked this episode, just let us know in the comments section. If you have any follow up questions from this episode or if you have a profile-specific questions that you would want us to evaluate, just leave a comment in the comment section with your detailed profile.
We’ll be happy to evaluate your profile to see if you have all that it takes to become a Data Scientist. So, I’m signing off from Episode 2 of Data Science and AI Weekly. My name is Manav and I look forward to seeing you in Episode 3 of Data Science and AI Weekly.
