Still Not Convinced?
With over 575 million registered users
and more than 260 million of those active on a monthly basis, LinkedIn is undoubtedly the
#1 professional networking platform. You have the opportunity to connect
with influencers, decision-makers, and leaders within your industry.
The social networking platform bridges
the gap between candidates and clients, which has led to more than 75% of
professionals now using LinkedIn. This will inform their decision when making a
change in their careers.
When a platform, such as LinkedIn,
becomes heavily populated with professionals working within the same
space, you need to focus on making yourself outshine the competition.
How To Optimise Your Data Science
LinkedIn Profile
Now that we’ve got an understanding of why you should be using LinkedIn, let’s take a look at each individual section of a profile layout. It’s time to make the most out of all that LinkedIn has to offer!
1. Creating a Professional Profile
Picture:
There are few things to keep in mind
when it comes to adding a profile picture.
You don’t have to necessarily wear a
suit, but it is recommended that choose a picture with formal attire.
The next thing is that the picture must
be clear and perfectly cropped and it is important that your photo is a recent
one.
2. The Headline and Career Summary
LinkedIn allows you to put a
description of what you do under your name. This should be a succinct and clear
definition of your skills or job. It should be simple enough to make anyone who
is visiting your profile for the first time to understand what it is that you
do.
The career summary goes under your
“headline”. While you are striving to make the recruiter understand what you
are currently doing, be sure to include skills or languages that you have
acquired. This should be very short and concise with the sole purpose of giving
a quick view about your skills or specialties without having the recruiter
scroll down to the ‘Featured Skills & Endorsements’ section. These details
make your profile informative without making it messy. The specialties that
you add to act as keywords. These are the words that you want people to find
with. Focus on 3-5 keywords, don’t go overboard with them and make it boring.
3. Relevant Work Experience
The Experience section is where many people
fill a lot of information when the information you provide here must be precise
and clear. Do not mention here every place that you have worked for, instead
mention the company names that you’re connected with and can be easily looked
up on LinkedIn. Mostly, when you type for your company name in the ‘Experience’
section, its name and logo should pop up.
When you are a data scientist, it is
imperative that this is clear and precise. The reason we stress more about this
is that LinkedIn is filled with data scientists who may have similar
experiences and skills. So, it might help if your list of experiences is less
confusing.
Here are some things you can include in
the experience section:
· Internships,
both paid and unpaid.
· Part-time
jobs.
· Entrepreneurial
or freelance work.
· LinkedIn
has a separate section for listing your accomplishments like projects and
certifications.
4. LinkedIn Profile URL
Create a profile URL. Allow others to
quickly identify you in search results by changing or customizing your public
profile URL. Just go to your ‘Profile’ then click on the profile URL which
appears on the bottom-left corner on the window. It should be something like
– https://www.linkedin.com/in/xyz-abc-245b5b42 by
default. Just click on it, add your name which is simple to read.
5. Data Science LinkedIn Skills
and Endorsements
This section is solely dedicated to
showcasing your strengths. List all your specialism with affirmations from your
peers.
A typical list for Data Scientist might
look like:
· C/C++
· Python
· HTML/CSS/JS
· Java/Android
· TensorFlow
· R
· SQL
· Keras
· jQuery
· Tableau
· AWS
· MATLAB
· Hadoop
· Spark
6. Listing your Accomplishments:
The Accomplishment section is for
listing all your projects, certifications, courses, patents etc.,
For data scientist along with other
accomplishments, you can mention your hackathon participations. Competitions
like the ones on Kaggle or Machine Hack carry greater importance than courses
certificates. This specifically comes in handy because these are bigger proof
of your skills.
7. Making Use of Recommendations
Recommendations give you a chance to
showcase the fact that you are more than face on the screen. Pay attention to
the recommendations that you have from the people you have worked with before.
This will further outline your portfolio and capabilities. While you’re
thinking about including every good recommendation you get, we suggest you only
to mention those which highlight your skills.
8. Listing Interests and Creating a
Network
When it comes to creating interest and
networking, LinkedIn is a great platform to meet people from similar fields.
You don’t have to join the groups strictly from Data Science. Join communities
and be active by posting about the latest news or trends related to Data
Science.
You will often find people sharing
their opinion on specialist subjects. Use LinkedIn to be conversational,
helpful and offer ideas.
9. Finding Recruiters
-Who can reach you?
Once you have set-up your profile,
there are some settings that you have to enable.
Allowing others to contact you through
InMail is vital because all the recruiters contact you through it.
Some additional tips to inculcate in
your profile:
1. Avoid
too many buzzwords.
2. Your
writing on your profile should convey not only your strengths but also your
personality.
3. Include
multimedia in your profile. Use links and upload images on your experience page
to enhance the experience there.
4. Include
some extracurricular activities, volunteer work and additional spoken or written
languages.
5. Include
your content like articles about your specialization, reactions to industry
trends etc.
6. Make
use of the Data Science LinkedIn groups
7. List your achievements and who it is that you want to connect with. Use every line within your profile description to sell what it is that you do and what you can offer.
