What does it_takes_to_be_a_good_data_scientist_2019_aim_simplilearn

What Does It Take To Be A Good Data Scientist?
By AIM & Simplilearn 1
By Analytics India Magazine & Simplilearn
WHAT DOES IT TAKE TO BE A
GOOD DATA SCIENTIST?

TABLE OF
CONTENTS
05
07
11
Executive summary
About the study
What kind of work does a Data Scientist work on?
13 How will you reach your goal of getting job in Data Science
15 Upskilling
17 Self study
19 Networking with industry insiders
21 Showcasing skills
23 How to appy for Data Scientist jobs
09 Foreword

EXECUTIVE
SUMMARY
Over the years, the term ‘data
scientist’ has evolved greatly.
From describing a person who
handles data, to a professional
who leverages machine
learning — this definition has
seen a great deal of change.
Now, circa 2019, there are
numerous blogs, Reddit pages
and Quora threads dedicated
to the discussion about “how
to become a good data
scientist”.
The spectrum of data scientist
roles and the myriad of duties
he/she has to perform is so
broad, that it is very difficult
to capture it under one single
definition.
Now, the data science sector
is flourishing to such an extent
that our earlier jobs study
revealed that there are
currently more than 97,000
job openings for analytics and
data science in India right
now.
It is true that the “hottest job
of the 21st century” has all
the buzz, glam and traffic, but
many enthusiasts are still
confused as to what this job
entitles. Fewer still,
understand, what it takes to
be a data scientist. Is it about
the skill set? Is it about the
education? Is it about the
company you work for?
Or is it all of the above?
DATA SCIENCE
DEFINITIONS
IN VARIOUS
DICTIONARIES
“A person employed to
analyse and interpret
complex digital data, such
as the usage statistics of a
website, especially in order
to assist a business in its
decision-making.”
“Data scientist is someone who can bridge
the raw data and the analysis – and make it
accessible. It’s a democratising role; by
bringing the data to the people, you make the
world just a little bit better.”
Data scientists are a new breed of analytical data expert
who have the technical skills to solve complex problems
– and the curiosity to explore what problems need to be
solved.
Data scientists are professionals who are well-rounded, data-driven
individuals with high-level technical skills. They are capable of
building complex quantitative algorithms to organise and synthesise
large amounts of information used to answer questions and drive
strategy in their organisations.
-OXFORD DICTIONARY
-SIMON ROGERS
-SAS
-BERKELEY SCHOOL OF INFORMATION

ABOUT THE
STUDY
This study was conducted in
association with Simplilearn.
The data for this study was
collected by asking
respondents to fill in a
survey created by Analytics
India Magazine about the
popular beliefs around what
it takes to be a good data
scientist. This included
various sub-topics such as
upskilling, employment, skill
set, and industry trends,
among others. We took
opinions from all those who
practice data science — from
professionals with less than
two years of experience to
CXOs — to get a thorough
idea of the working
environment in this growing
field.
Our survey was met with
much enthusiasm — and we
got some great insights from
it. Some of them were
expected, and many of them
were real eye-openers.

FOREWORD
In the past, data did not play a
critical role in shaping an
organization’s future, like it
does today. The advent of big
data is bringing about a
transformation at the very core
of the business process.
With the right insights, data
scientists have the potential to
completely transform an
organization’s growth
trajectory.
Reports suggest that the
global volume of data is set
to grow from 33 zettabytes
in 2018 to 175 by 2025. The
study also speculates that in
2025, each connected per-
son will have at least one data
interaction every 18 seconds.
This data, which constitutes
both structured and
unstructured data will need to
be stored, processed, and
analyzed in order for it to
deliver its complete value.
This throws up a huge
opportunity for data scientists;
making data science a
lucrative career option. As
per a report by a job search
website, postings for data
science jobs on the website
have grown by a whopping
344% as compared to five
years earlier. Also, the number
grew 29% year-over-year as
of December 2018.
Data science is hardly a
monolithic field. Data
scientists are often involved
in various aspects of the
process right from data
collection to analysis to
recommendations. So, the
skills required are likely to be
diverse too. For profession-
als who are keen to become
data scientists, the question
that then arises is, what does
it take to build a successful
career in data science? What
makes a good data scientist?
There isn’t necessarily a
straightforward answer
because the field is vast and
rapidly evolving. The skillset
required is fairly diverse. Of
course, the right technical
skills are important. Data
scientists are generally
expected to have a degree
in computer science and be
conversant with programming
languages such as Hadoop,
Python, and Java.
Apart from programming, the
ability to learn quickly, adapt to
changes, communicate clearly,
and understand the big picture
are equally crucial. Also, while
the technologies will evolve
over time and data analysis
techniques might change, the
ability to think critically will
always be in demand. Domain
expertise is also important
especially when it comes to
asking the right questions and
understanding the right
problems to be solved. In
addition, a certain amount
of business acumen is much
needed.
This study will shed more light
on the roles and responsibili-
ties of data scientists today. At
the same time, it will talk about
the current state of the industry
in terms of the jobs available,
the industry’s hierarchy model,
and the recommended path for
upskilling. Basically, the report
is intended to provide some
useful insights on the
qualities that an ideal data
scientist should encompass.
We trust that readers will find
the report interesting and
useful.
- Krishna Kumar, CEO, Simplilearn

DATA SCIENCE
SKILL SET
In an interaction with Analytics
India Magazine, Dr Krishnan
Ramaswami, Head of Data
Science at Tesco, listed out
the ideal skills required in a
successful data scientist.
1. Mathematical & statistical
knowledge
2. Good knowledge of
machine learning algorithms
3. Awareness on programming
languages like Python and
R which are more tuned for
data science
4. Handling large datasets
5. Domain knowledge
6. Problem-solving ability
Dr Ramaswami also
emphasised on hands-on
experiences. He said,
“Participation in any machine
learning competitions would
be an added advantage as
they serve as additional
validation of their skills.
Experience of developing any
real-life problems either during
their course work or
exposures through projects is
also beneficial.”
In this study, Analytics India
Magazine, in association with
Simplilearn, is taking a
deeper look at what steps
data science professionals
take to kick-start and further
themselves in their careers.

0
All of the above
20% 40%
Business Interaction
Database Engineering
Coding
Visualisation
Modelling
PERCENTAGE DISTRIBUTION OF THE KIND OF WORK THAT DATA SCIENTISTS
PREFER TO WORK ON
WHAT KIND OF WORK DOES A
DATA SCIENTIST WANT TO
WORK ON?
This question is of key
importance to almost all data
scientists, because as this is
a nascent field, there are still
some grey areas about the
definitions. That is why, the
first question we asked
during our exhaustive survey
was about the kind of work
the data scientists preferred to
do.
• A large chunk of 36.9% of
respondents said that they
would ideally like to do
more of modeling
• 34% of the respondents
said that they would
also like to do business
interaction and draw
business insights
• However, 55.3% of the
respondents said that
they were interested in
all of the aspects in data
science — modelling, data
visualisation, coding,
database engineering and
business interaction

0 20% 40%
All of the above
Showcase skills
Network
Update skillset
PERCENTAGE DISTRIBUTION OF THE KIND OF WORK THAT DATA SCIENTISTS
PREFER TO WORK ON
HOW WILL YOU
REACH YOUR GOAL OF
GETTING A JOB IN
DATA SCIENCE?
As mentioned earlier, the
demand for data science
across the industries is real.
Over the past few years, the
domain has been experiencing
a rapid rise in jobs across the
world and India is one such
country that is experiencing a
data explosion. However, there
is also a disparity between the
number of jobs available and
the number of applicants.
Data science aspirants say
that getting a job is difficult,
and noted enterprises com-
plain that the biggest problem
they face is of talent crunch —
especially in data science.
But why is that?
That’s why, when we asked
about what was the best way
to get ahead in their career, we
got very interesting responses.
• 41.7% respondents said
that they would like to
update their skillsets
• And 24.3% of the
networking more with
industry insiders was the
way to move ahead in their
careers

19%
Take a break,
study full time
PERCENTAGE DISTRIBUTION OF HOW DATA SCIENCE PROFESSIONALS PREFER TO
UPSKILL THEMSELVES
48%
Self study
33%
Online courses
UPSKILLING
Most companies and
business leaders are posed
with the question of how to
build capabilities in an
organisation so that they can
ride the wave of digital
transformation. Companies
are desperately looking
for people with skillsets
that meets the need of the
growing technological
demands.
When we asked our
respondents what was their
preferred choice of upskilling,
the results were interesting.
• Over 33% of our
would prefer to register for
an online course
said that they would like
to take a break from their
current work or study
schedule and pursue
data science as full-time
education.
• About 48% of the
they would like to study
on their own, with the help
of MOOCs and other free
resources.

0
Sponsored course
25% 50%
Learn from others
MOOCs
Books
YouTube
PERCENTAGE DISTRIBUTION OF THE KIND OF SELF-STUDY THAT RESPONDENTS
LIKE TO PREFER
SELF
STUDY
In this competitive day
and age, enterprises are
focussing on not just
looking for candidates
trained in a single skill but
an individual who knows a
cluster of skills which will be
relevant for more number of
years. Some of the skills that
are currently picking up are:
• Automation
• RPA
• Robotics
• Cybersecurity
• Artificial intelligence
• IoT
• Connected devices
• FinTech
• Blockchain
Our respondents had
numerous options when it
came to self-study.
• For instance, 67% of our
respondents preferred to
take free online courses in
data science
• Over 62% of our
respondents preferred to
watch YouTube videos and
tutorials to learn more
• And almost 44% relied on
books

0
Social media
20% 40%
Online groups
Webinars
LinkedIn
Meetups
Conferences
PERCENTAGE DISTRIBUTION OF HOW DATA SCIENTISTS LIKE TO NETWORK WITH
INDUSTRY INSIDERS
NETWORKING WITH
INDUSTRY INSIDERS
Building social capital by
engaging in social groups is a
crucial aspect of strategising
career success. Networking
helps in accomplishing
contacts that can be helpful
in getting recommendations,
and in turn, better job
opportunities.
Data scientists’ career also
hinges on making meaningful
contacts and creating lasting
bonds with interesting and
influential people. There are
many avenues for the same,
but our respondents had
interesting insights regarding
this:
• 68% of our respondents
said that professional so-
cial media portal LinkedIn
was their choice of tool
to start networking in this
ever-growing profession
• Over 62% of our
attending conferences
with interesting subject &
like-minded people was
immensely helpful in their
careers
• Blogs and social media
were endorsed by 55% of
our respondents
• And meetups was another
helpful avenue for 54% of
the participants

0
Blogs
25% 50%
Events
Github
Hacakthons
PERCENTAGE DISTRIBUTION OF HOW DATA SCIENTISTS LIKE TO NETWORK WITH
INDUSTRY INSIDERS
SHOWCASING
SKILLS
For a data scientist,
showcasing his/her abilities
in coding and other software
capabilities is crucial. An
important part of data
science is to stay relevant in
the industry by showcasing
your interest, expertise and
unique opinion in all as many
relevant subjects as possible.
Our participants had
interesting insights
regarding this.
• 63% of our respondents
said that the best way to
showcase skills would be
through hackathons
• 59% said that keeping their
Github page updated and
active was the way to go
• And over 53% of the re-
spondents said that
blogging about their
experiences and best
practices was the key to
update the community and
stay connected with them

BEST WAYS TO APPLY FOR DATA SCIENCE
JOBS
EDUCATION
CITY
50%
Bengaluru
20.2%
Delhi NCR
7.1%
Hyderabad
9.6%
Mumbai
12.5%
0.6%
48.5%
Post graduation
45.6%
Graduation
5.9%
14.4%
Move
laterally
12.5%
Recruitement
Consultants
15.4%
Social media
11.5%
Ears to the
ground via
friends/
colleagues
WORK EXPERIENCE
19.2%
Student
9.6%
15+ years
3.6%
10-15 years
9%
5-10 years
16.3%
2-5
years
42.3%
0-2 years
HOW TO APPLY FOR
DATA SCIENCE JOBS
As tools and techniques in
data science are evolving,
jobs in this sector are
maturing and gaining more
and more prominence. The
number of openings that
companies have for data
science roles is also on an
all-time high.
That is why, it makes a huge
difference as to what company
you’re applying to, and what
avenue you’re using to
approach it.
• Almost 46% of our
apply for job openings
through job portals like
Naukri, Monster, Shine,
etc. among others.
said that they preferred
connecting to companies
via social media
• 15% of the participants
said that they also were
in touch with recruitment
consultants for jobs
Pune
Kolkata
Others

© 2019 Analytics India Magazine Pvt Ltd and/or its affiliates. All rights reserved.
Images or text from this publication may not be reproduced or distributed in any
form without prior written permission from Analytics India Magazine.
The information contained in this publication has been obtained from sources
believed to be reliable. Analytics India Magazine disclaims all warranties as to
the accuracy, completeness or adequacy of such information and shall have no
liability for errors, omissions or inadequacies in such information. This publication
consists of the opinions of Analytics India Magazine and should not be construed as
statements of fact. The opinions expressed herein are subject to change without notice.

CONTACT US
ANALYTICS INDIA MAGAZINE
#280 , 2nd floor, 5th Main,
15 A cross, Sector 6 , HSR layout
Bengaluru, Karnataka 560102
SIMPLILEARN
NALANDA, 53/1 C, Manoj Arcade,
24th Main Road, Sector 2, HSR Layout
Bengaluru, Karnataka 560102

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