opportunities in Data Science and AI
are growing exponentially and in this
video
I am going to talk about the difference
between two important roles in this
field which is Data Scientist
and Machine Learning Engineer and we
will evaluate it on
three fronts which is - Job duties, the
skill set
and the salaries . So let's start with the
Job duties.
The role of Data Scientist is to
follow the complete Data Science Process
or a Data Science Pipeline
which is understanding a business
problem,
collecting data, doing exploratory 19 00:00:38,239 --,> 00:00:41,840 data analysis
building a model and drawing the
insights.
This is the duty of a Data Scientist.
They follow all these steps
and then they represent these insights
to the stakeholders.
So their job involves lot of creativity,
domain knowledge, understanding business
problem,
data cleaning techniques and then of
course Machine Learning
model building and then generating
insights
but often Data Scientist would
build this models in dev environment and
when they have to
deploy this to production, they take help
of Machine Learning Engineers.
So now Machine Learning Engineers are
responsible for
maintaining and creating the machine
learning infrastructure
so that they can deploy the models built
by
Data Scientist to production and not
only they can deploy
but to scale them. So when it comes to
enterprise solution,
you need to think about scaling the
system
using distributed computing so that you
can sell the needs of
client clients in a time efficient
manner.
All of this activity is done by Machine
Learning Engineer.
So you can see that Data Scientist are
kind of the users of
Machine Learning infrastructure that is
built by Machine Learning Engineers.
And when I say deploying it to
production it could be deploying it to
wearable device.
You might have a wearable device which
is tracking your heart beats and using
some
Machine Learning model for doing some
prediction.
So how do you deploy that model
on little wearable device which has less
memory and computation resources
so that it performs really fast.
Think about autonomous cars . So tesla
cars
can detect objects and it can do
autonomous driving
so that car has little computer sensors
and those are running those models . So
how do you run those models in
efficient way? How do you take care of
errors?
All of those things are the
responsibilities
of Machine Learning Engineer think about
technical skills,
Data Scientist and Machine Learning
Engineer role
are quite overlapping . So many times if
you go to small companies
Machine Learning Engineers might be
doing work of Data Scientist and vice
versa.
So there is lot of overlap but overall
there are few common skills such as
of course knowing about Machine Learning,
predictive modeling,
statistics and math, Python these are
common skills that both Data Scientist
and Machine Learning Engineer have
but on top of that, our Data Scientist
are
good in terms of telling the data
stories,
creativity, understanding business
problems. So many times you will see
Data Scientist will have a strong
domain knowledge. For example if you are
in finance,
a person might be a
CFA you know, he might have a strong
finance background and then that person
will learn technical background and
become a Data
Scientist. Machine Learning Engineer on
the other hand are
core Software Engineers they are very
good in data structures algorithms.
They understand computer science you
know, it's kind of hard to become
a Machine Learning Engineer without
having a computer science background.
They understand memory, CPU utilization,
distributed computing,
fault tolerance, log analysis they know
all of those cool computer science
techniques. In terms of programming
language
Data Scientist are good in either
Python
or R whereas Machine Learning Engineers
will be good in
C++, Java, Python
Scala etc. Often Machine Learning
Engineers
build their own algorithms you know. When
they write, let's say
they are not happy with the default
implementation of decision tree
from scale on, they might come up with
their own implementation with little
tweaks
and those implementations, they will
generally do it in either Java or C++,
they want the efficiency. They might use
Julia as well
but you can see that they write low
level code whereas
Data Scientist work at a little upper
level
where they will use the the modules or
the libraries
created by Machine Learning Engineers in
order to solve those problems.
Data Scientist often use BI tools such
as Power BI Tableau
for doing data analysis. I have seen many
times Data Scientist don't use
ML at all. You know they they can do data
science
using Excel or Python Pandas and
Power BI whereas Machine Learning
Engineers
their core role is to do machine
learning. So
they will be doing Machine Learning, Deep
learning all the time whereas Data
Scientists,
Machine Learning is one of the tools for
doing Data Science
hence Data Scientist might not be using.
There might be a scenario where you know
as a Data Scientist you might not use
Machine Learning techniques
or deep learning for six months.
For salaries as per indeed.com,
Data Scientist on average make
122,000 a year whereas Machine Learning
Engineers make 148,000 a year
in India, Data Scientist make
around
750,000 rupees per annum
on average whereas our Deep
Learning Engineer
they're saying it's same but don't go by
this indeed.com numbers because
they are average across different cities,
different experience levels and so on.
In reality, the salary range that you get
actually varies too much. It varies based
on your
skill set, your the city, the company
that you are getting an offer from and
just to go over
some of these examples I'm going to go
through this
website called teamblind.com
where people post their offers. You know
if the person has two offers from
different companies and he wants to take
other people's opinion,
they will post these offers and I looked
at some of these, these are like real
numbers I have friends working for big
fat companies, so I
know that these numbers are
real.
So let's go over some of these
numbers so you get a better idea.
You can go to teamblind.com and search
for any topic let's say I'm interested
in
Machine Learning Engineer and it will
show me
different posts related to machine
Engineers and now these are not
necessarily
all job offers, but they could be general
discussion about
Machine Learning Engineer but it happens
that,
many of these discussions are related to
job offer.
For example here one person got a job
offer
from Twitter and Square as a Machine
Learning Engineer in both the companies
and he's comparing the offers . So in
Twitter
he is offered 330,000 dollars
per year whereas in Square it is 390,000 dollars
per year. YOE means year of experience.
Now this person has
nine years of experience. Machine
Learning career is
fairly new . So all nine years I don't
think will be in Machine Learning field
it will be
software engineering and recently he
might have become Machine Learning
and they get offer like this. Now this
is not an exceptional offer, people get
even more
money than this and the reason I want to
show you all of this
is because the the salaries vary too
much,
based on your experience, based on the
company, the city, etc.
Here is another offer from Linkedin.
The offer is around 200,000
dollar
but look at year of experience, the
person is fresh graduate. Only one and
half year experience
you get 200,000 dollar a
year
base is 145 and then 10 percent
bonus and RSU is Restricted Stock
Units.
So 250,000 of stock unit
over a period of four years. Now
the tech stocks are booming,
stocks are going crazy high and people
are earning
so much money. Here is another offer
for Square Machine Learning Engineer and
the person is getting total 315,000 dollar
a year at Amazon
and with the Amazon stock growth in 2020
he'd be making 420,000 dollar
a year. Now this is Level 6 at Amazon
ofcourse few years of experience.
So you see that Machine Learning
Engineer
salaries could be, if you're in
product-based company could be
more than 300,000 dollar, it could be 400 it
could be even
500,000 dollar a year. Yes, half a million dollar
a year. This is the reality
people are not posting lies here and how
do I know?
Because I have contacts, I have friends
who are working in these companies
and I know that these are all the facts
okay no exaggeration.
Now let's compare Data Scientist salary
So here someone is talking about
Facebook Data Scientist and the person
has an offer
with TC means total compensation
320,000 dollar a year in
Los Angeles. He has another offer from
Uber
390,000 dollar a year
and the year of experience is 10 years.
Uber Data Scientist in San Francisco,
three years of experience,
120 and 20 like
140,000 dollar
plus 80000 dollar
per year stock option . So around
200,000 dollar
a year for uber Data Scientist. Another
one
for Facebook Data Scientist five years of
experience
160 base and 15 percent bonus
200,000 dollar stock units
over a period of four years . So let's say
50k per year . So this will be
little more than 200,000 dollar. So you can see
that
Machine Learning Engineers are getting
paid much higher than Data Scientist
but if you're working for fang companies
minimum you can expect 200,000 dollar
and based on experience, if you are
PhD for example if you done a research
paper
I have heard in Google you can get up to
700,000 dollar
a year . So go to this teamblind.com
explore different conversations, explore
different offers that people are having.
The reason I am showing this to you is
to show you the fact that the
job the salaries vary too much based on
the company to company, based on the
region, based on your experience
it can vary anywhere from
100,00 dollar
to 800,000 thousand dollar okay . So
the sky is the limit. If you are very good,
skillful, you can earn hell lot of money.
The world is full of opportunities. I
hope that clarifies the difference
between Data Scientist and Machine
Learning Engineer
based on your skill set and interest
level, you can
choose to pursue one or the other
career
and of course if you're Data Scientist
you can switch to ML or
ML person can switch to Data Scientist
so you always have that flexibility
You just saw that from the teamblind
review people earn hell lot of money.
I was talking to my wife and I was
telling her that,
she works in a hospital, it's like
Machine Learning Engineers make
more money than you know surgeons, doctor
surgeons.
So the the career is
very hot and in demand . So if
you're interested in learning about Data
Science Machine Learning I have many
videos on my
on my youtube channel where I teach
Machine Learning, Python, Data Science
Data analysis skills, Tableau Power BI
for free and all these tutorials are
designed for complete
absolute beginners. You don't need any
background.
So I will go over all the basics in this
tutorials, then I
do theory, then I write code and also I
have exercises
and I have interesting giveaways
and challenges
are going on the website
skillsbasics.com
So check out the content. If you like
this video,
give it a thumbs up and share it with
your friends. I will see you in next
video. Thank you.