My first question to you is, what
are the different data related profiles? Under that umbrella, there are a lot of different kinds of roles,
data analytics or business analytics. There is data scientist, there is decision scientist,
which I am right now. Decision scientist? Decision scientist, yeah. Out of all these roles,
in what roles can freshers apply? That's a good question. So there are a few
roles that have lesser friction to enter, which means it's less harder to get into, the data
analytics role or the business analytics role or the business intelligence engineer role. What is the work that you do, being a data analyst
or a business analyst or a data scientist? Usually what the data analyst or business analyst does here,
they hit the database, whichever database the company works with,
they clean the data, make sure the data is in the required format,
they aggregate the data. What are the average entry-level salaries if
a fresher wants to get into these roles? On average, I think the average salary you can expect for a data
analyst is between 6 to 8 or 6 to 9 for a fresher role. For my level, an applied scientist can easily,
in a good company, yeah, 80 to 1 CR was what I would say. Everybody aimed for an applied scientist. Now let's talk about a detailed roadmap. Let's talk about the preparation part of it. Your biggest focus has to be on SQL. But if your SQL is bad,
you're not getting through. End of story. What should come in the resume
so that it is visible for the recruiters? Every role has about 1000 applicants. When I recruit people, I will spend maximum about
10 to 12 seconds to look at the resume. What I do
usually is highlight the skills section. What is the right strategy to apply? Apply and request for a referral. So you
think getting a referral is better than… 100%. 100%. So now a very important question. Is it true that you don't need DSA at all? Never have I heard of
a situation when they've asked for DSA. I don't even know if you
know about that famous Walmart problem. Walmart noticed that there was a high correlation
between beer and diaper sales. So Nandini, tell me, what do you think will be the
demand of the data field in the coming future? Compared to other roles, I still think any data
role has a lot of demand in the market. You think the demand is going to increase? I think it's going to definitely increase. And if
you combine it with the software skills, so that probably you put yourself at even more leverage,
a better leverage. All right. Awesome. Good news for you folks. Hi, everyone. Welcome to a new episode. So today's
episode is going to be around data. We'll be looking at all the
different profiles under this umbrella. What kind of work is there. How can we apply? Freshers are eligible for which roles which profiles are smooth to enter? Which profiles are difficult to crack? We're going to discuss all these things. So watch till the end
if you are seriously preparing for it. So today I have Nandini with me. Nandini is my teammate from Google. Before Google, she was
working as a data scientist in LinkedIn and have a pretty
good experience of around eight years. So all these questions will be answered. Watch the podcast till the end. You can follow Nandini on her Instagram. The link is in the description. And now let's get started. So hi, Nandini. How are you? I'm good. How are you? I'm also doing great. So Nandini, a lot of freshers nowadays, they are
mostly looking for data related profiles. Mainly there are two reasons for that. One is
they're not that good in data structures and algorithms and they think
DSA is not required in data profiles. Other reason is we have been listening a lot of
news that data profiles are in hype nowadays. A lot of openings are there and the salaries
are also as good as software engineers. So we're
going to discuss about all these things. My first question to you is what
are the different data related profiles? So I think
that's a question a lot of people have. They think, you know,
when it comes to data is just like one kind of profile, but that's
not the case under the data itself. There are a lot of roles under that umbrella, there
are a lot of different kinds of roles. Let's start with
data analytics or business analytics. There is business intelligence engineer
or business intelligence analyst. There is data scientist, decision scientist,
which I am right now. Decision scientist. There is MLops engineer,
which is more engineering heavy. There is applied scientist,
which is more research heavy. Then there are data engineers,
which are more backend heavy. So under the data umbrella, there are quite
a few different kinds of data roles. Out of all these roles,
in what role can freshers apply? That's a good question. So there are a few
roles that have lesser friction to enter, which means it's less harder to get into. And if I had to talk about those roles,
it's mostly the data analytics role or the business analytics role or
the business intelligence engineer role. I would definitely say these are more easier,
lesser friction entry roles. So if you had to apply,
there are more companies that
