
English: 
Welcome to this 3-6-5 Data Science special,
where you’ll learn everything you need to
know to land an entry-level job in Data Science!
As one of the fastest-growing industries over
the last decade, Data Science has become an
extremely appealing career path. That path,
however, needs to start somewhere. So, if
you are watching this video – you’ve got
questions. Well, we are here to give you the
answers and then point you to some extra resources
that will help you prepare for data science
success.
We’ll go over education, experience, skills
and finish up with a cohesive plan on the
steps you need to take to start your journey
as a Data Scientist. Of course, all the information
is based on empirical research, statements
by employers in data science, and a dash of
our personal experience.
So, let’s begin, shall we?
In previous videos on our channel, we’ve
discussed the best degree for an aspiring
data scientist. To recap: any form of post-graduate

English: 
welcome to this 365 data science special
where you'll learn everything you need
to know to land an entry-level job in
data science as one of the fastest
growing industries over the last decade
data science has become an extremely
appealing career path that path however
needs to start somewhere so if you're
watching this video you've got questions
well we are here to give you the answers
and then point you to some extra
resources that will help you prepare for
data science success we'll go over
education experience skills and finish
up with a cohesive plan on the steps you
need to take to start your journey as a
data scientist of course all the
information is based on empirical
research statements by employers and
data science and a dash of our personal
experience so let's begin shall we
in previous videos on our channel we've
discussed the best degree for an
aspiring data scientist to recap any

English: 
degree in a quantitative field gives you a
pretty good chance of success, with Computer
Science being the most-represented major.
Apart from an education, you also need some
sort of experience credentials to your name.
To understand the methodology we used, you
can check out the article linked in the description.
For reference, the results suggest that roughly
35% of current Data Scientists have already
had a job in the same position, which is actually
fantastic.
Woah, woah, woah… but how is this good news?
Well, the remaining 65% had a different occupation
prior to that. Therefore, roughly 2 out of
every 3 data scientists are on their first
data scientist job in the field. Therefore,
it’s safe to say that becoming a data scientist
is a very achievable goal.
However, don’t expect to become a data scientist
right after school. A mere 2% of all data
scientists started off with no previous position

English: 
form of postgraduate degree in a
quantitative field gives you a pretty
good chance of success with computer
science being the most represented major
apart from an education you also need
some sort of experience credentials to
your name to understand the methodology
we used you can check out the article
linked in the description for reference
the results suggest that roughly 35
percent of current data scientists have
already had a job in the same position
which is actually fantastic whoa whoa
whoa whoa but how is this good news well
the remaining 65 percent had a different
occupation prior to that therefore
roughly 2 out of every 3 data scientists
are on their first data scientist job in
the field
therefore it's safe to say that becoming
a data scientist is a very achievable
goal however don't expect to become a
data scientist right after school 2% of
all data scientists started off with no
previous position on the resume this
number in itself sounded suspiciously

English: 
high to us either way to land even an
entry-level position you need some
previous experience elsewhere this is a
testament to how demanding the position
of a current day data scientist is
nowadays demanding and hard to get
but not impossible so what step should
you take
according to employers and recruiters if
you want to succeed in the field you
also need to know three things the tools
the data and the business let's break
this down
knowing the tools means confidence in
working with the most popular software
on the market
those are undoubtedly athon r or better
yet both with a bit lower priority but
still extremely important are SQL and
visualization software such as power bi
and tableau finally it is important to
note that Excel is still a main
prerequisite in any job description in
the field now if you feel you need to

English: 
on their resume. This number in itself sounded
suspiciously high to us. Either way, to land
even an entry-level position, you still need
some previous experience elsewhere.
This is a testament to how demanding the position
of a current day data scientist is nowadays.
Demanding and hard to get, but not impossible.
So, what steps should you take?
According to employers and recruiters, if
you want to succeed in the field, you also
need to know three things: the tools, the
data and the business.
Let’s break this down!
Knowing the tools means confidence in working
with the most popular software on the market.
Those are undoubtedly R, Python, or better
yet - both. With a bit lower priority but
still extremely important are SQL and visualization
software, such as PowerBI and Tableau. Finally,
it is important to note that Excel is still
a main prerequisite in any job description
in the field.

English: 
strengthen your data science skill set
we've got you covered we've created the
365 data science program to help people
enter the field of data science
regardless of their background we have
trained more than 350,000 people around
the world and are committed to continue
doing so if you are interested to learn
more you can find a link in the
description that will also give you 20%
off all plans if you're looking to start
learning from an all around data science
training okay back to the key
requirements for entry-level data
scientists next up is knowing the data
this means you need to understand where
your data is coming from what are the
best ways to process and pre process it
and most importantly how to extract
actionable insights from it therefore
you need some coding pedigree regardless
of whether it's in our Python or another
scripting language the statistical and
analytical skills are there to help you
understand and interpret the results
before translating their raw numbers

English: 
Now, if you feel you need to strengthen your
data science skillset, we’ve got you covered.
We’ve created ‘The 365 Data Science Program’
to help people enter the field of data science,
regardless of their background. We have trained
more than 350,000 people around the world
and are committed to continue doing so. If
you are interested to learn more, you can
find a link in the description that will also
give you 20% off all plans if you’re looking
to start learning from an all-around data
science training.
Okay! Back to the key requirements for entry-level
data scientists!
Next up, is knowing the data. This means you
need to understand where your data is coming
from, what are the best ways to process and
pre-process it, and most importantly, how
to extract actionable insights from it.
Therefore, you need some coding pedigree,
regardless of whether it’s in R, Python
or another scripting language. The statistical
and analytical skills are there to help you
understand and interpret the results before

English: 
into insights usually to land an
entry-level job you don't need to excel
in all categories and being okay in two
of the three is fine as long as you're
great at programming finally it's
crucial that you know the business
before you apply for a job in a given
company you must find out which aspects
of data science and what skills are
necessary to land a position there and
by all means having market expertise in
the specific
field is always a bonus so the more
holistic your understanding of the data
and the industry the more well-suited
you are for the position overall
employers are looking for somebody with
good coding statistical and analytical
skills aren't we missing something of
course
employers are achievement oriented so
they're always looking for certain
transferable skills in a candidate that
add value to the company taking

English: 
translating the raw numbers into insights.
Usually, to land an entry-level job you don’t
need to excel in all categories and being
okay in 2 of the 3 is fine… as long as you’re
great at programming. 😊
Finally, it’s crucial that you know the
business. Before you apply for a job in a
given company, you must find out which aspects
of data science and what skills are necessary
to land a position there. And, by all means,
having market expertise in the specific field,
is always a bonus. So, the more holistic your
understanding of the data and the industry,
the more well-suited you are for the position.
Overall, employers are looking for somebody
with good coding, statistical, and analytical
skills.
Aren’t we missing something?
Of course, employers are achievement-oriented,
so they’re always looking for certain transferrable
skills in a candidate that add value to the
company.

English: 
Taking initiative, setting challenging goals,
and making efforts to exceed those goals are
some examples of transferrable skills you
should develop. Interpersonal skills also
translate easily across various industries
and contexts, so make sure you got that covered.
Other highly appreciated skills in this category
include the ability to learn from experience
and be the propeller of positive changes,
independence, self-direction, and accountability.
Therefore, make sure your resume includes
projects or internships where you worked with
others, on top of some evidence of your proficiency
in coding. Your statistical and analytical
credentials can always be tested with an on-sight
examination or an academic transcript, so
focus on the interpersonal and programming
skills when constructing your resume.
For the full list of skills, check our free
Data Science career guide. And, if you want
to learn more about what you should and shouldn’t
include in your resume, check out our data
science resume guides. Links are in the description.
Alright!
So, we discussed what you need to know, and
what skills you need to have, but now it’s
time for the what you need to DO part.
In highly competitive fields, such as Data

English: 
initiative setting challenging goals and
making efforts to exceed those goals are
some examples of transferable skills you
should develop interpersonal skills also
translate easily across various
industries and contexts so make sure you
got that covered other highly
appreciated skills in this category
include the ability to learn from
experience and be the propeller of
positive changes independence self
direction and accountability therefore
make sure your resume includes projects
or internships where you work for others
on top of some evidence of your
proficiency in coding for the full list
of skills check our free data science
career guide and if you want to learn
more about what you should and shouldn't
include in your resume check out our
data science resume guides links are in
the description all right so we
discussed what you need to know what
skills you need to have but now it's
time for the what you need to do part in
highly competitive fields such as data

English: 
Science, who you know could be just as important
as what you know. This is especially true
when you’re trying to break into the field
and find somebody who is willing to give you
a chance, even at a Junior position. Getting
a recommendation from your previous boss,
or a referral from an employee of the company
you are currently applying at, is a sure-fire
way to boosting your chances of getting hired.
And the tried and tested way of getting these
is through networking.
One good approach is to use Handshake and
similar sites, where alumni from your school
post job ads. This way, you can find interesting
potential employers who you want to interact
with. Drop them an e-mail, ask them for an
informational interview, give them your details
and ask specific questions about what their
company does. By doing so, you’re making
a solid good impression because: A) you know
or you want to learn the business, and B)
you’ve done your research.
Sometimes, you won’t be able to get direct
contact information through the website, so

English: 
science who you know could be just as
important as what you know this is
especially true when you're trying to
break into the field and find somebody
who is willing to give you a chance even
at a junior position getting a
recommendation from your previous boss
or a referral for an employee of the
company you are currently applying at is
a surefire way to boosting your chances
of getting hired and the tried and
tested way of getting these is through
networking one good approach is to use
handshake and similar sites or alumni
from your school post job ads this way
you can find interesting potential
employers who you want to interact with
drop them an email ask them for an
informational interview give them your
details and ask specific questions about
what their company does by doing so
you're making a solid good impression
because a you know or you want to learn
the business and be you've done your
research sometimes you won't be able to
get direct contact information through

English: 
the website so you can check out your
school's alumni directory you should be
able to find at least an email a phone
number or a LinkedIn profile and all you
have to do next is reach out
alternatively you can meet people in the
field by going to local conferences or
lectures about data science universities
and colleges frequently organize events
of the sort which are often open to the
general public
in addition independent data science
societies also sponsor or organize
control group meetups where they discuss
the applications of des and specific
fields like medicine or finance for
example just remember the more invested
you look the higher the chance that
these people would want to keep in touch
so try to stay enthusiastic and curious
of course knowing the right people will
get you far but in most cases won't get
you the job even with a referral or
recommendation you still have to go
through a job interview your potential
employers can always test your

English: 
you can check out your school’s alumni directory.
You should be able to find at least an e-mail,
a phone number or a LinkedIn profile, and
all you have to do next is reach out.
Alternatively, you can meet people in the
field by going to local conferences or lectures
about Data Science. Universities and colleges
frequently organize events of the sort, which
are often open to the general public. In addition,
independent Data Science societies also sponsor
or organize control-group meetups where they
discuss the applications of D-S in specific
fields – like medicine or finance for example.
Just remember, the more invested you look,
the higher the chance that these people would
want to keep in touch, so try to stay enthusiastic
and curious.
Of course, knowing the right people will get
you far, but in most cases – won’t get
you the job. Even with a referral or recommendation,
you still have to go through a job interview.
Your potential employers can always test your

English: 
statistical skills with a written exam
and your programming skills with a
remote task however you only get the
face-to-face interview to present your
coherent communication skills so make
sure you highlight them in the best
possible way of course data science and
corporates multidisciplinary aspects of
various fields so it can't be difficult
to prepare for everything that is why we
created a free booklet with the most
common real-world interview questions
for DES and their answers think of this
as our data science equivalent to
cracking the code albeit a little bit
smaller
you can find a link to this resource in
the description as well right
after explaining everything let's
quickly summarize what you need to do to
land an entry-level job as a data
scientist for starters you should earn
at least a graduate degree in a
quantitative major like computer science
then you need to gain experience in a
field tangent to data science

English: 
statistical skills with a written exam and
your programming skills with a remote task.
However, you only get the face-to-face interview
to present your coherent communication skills,
so make sure you highlight them in the best
possible way. Of course, data science incorporates
multi-disciplinary aspects of various fields,
so it can be difficult to prepare for everything.
That is why we created a free booklet with
180 of the most common real-world interview
questions for D-S and their answers. Think
of this as our Data Science equivalent to
“Cracking the Code”, albeit a little bit
smaller. You can find a link to this resource
in the description as well.
Right!
After explaining everything, let’s quickly
summarize what you need to do, to land an
entry-level job as a Data Scientist.
For starters, you should earn at least a graduate
degree in a quantitative major like Computer
Science. Then, you need to gain experience
in a field tangent to Data Science, so a job
as an analyst or in I.T. is a good way to

English: 
go about it. An internship is also a viable
option, if you’re still studying.
Knowledge about coding, working with data
and the line of work you are interested in
is vital too, so ensure your resume showcases
all of that. Also, try to highlight some essential
transferrable skills in your resume, like
drive for the business and ability to work
in cross-functional teams. Conduct some networking
and try to earn a recommendation or referral
for a specific position. On a final note,
make sure to showcase certain immeasurable
qualities you possess, like communication
skills and curiosity during the interview.
In our opinion, doing all of this will give
you a great shot at securing an entry-level
job as a Data Scientist.
If you enjoyed this video, don’t forget
to hit the “like” or “share” button!
And if you’d like to become an expert in
all things data science, subscribe to our
channel for more videos like this one.
Thanks for watching!

English: 
so a job as an analyst or NIT is a good
way to go about it an internship is also
a viable option if you're still studying
knowledge about coding working with data
and the line of work you're interested
in is vital to so ensure your resume
showcases all of that also try to
highlight some essential transferable
skills in your resume like drive for the
business and ability to work in
cross-functional teams conduct some
networking and try to earn a
recommendation or a referral for a
specific position on a final note make
sure to showcase certain immeasurable
qualities you possess like communication
skills and curiosity during the
interview in our opinion doing all of
this will give you a great shot at
securing an entry-level job as a data
scientist if you enjoyed this video
don't forget to hit the like or share
button and if you'd like to become an
expert in all things data science
subscribe to our channel for more videos
like this one thanks for watching
