Home / Blog / Data Science / How to Market your Profile on LinkedIn - For Aspiring Data Scientists

How to Market your Profile on LinkedIn - For Aspiring Data Scientists

  • by Mr. Enoch
  • May 31, 2020
  • 417

How to Market your Profile on LinkedIn

Make sure you add up your resume in your LinkedIn profile. Add your contact number in your profile as a headline, it helps the recruiters reach you directly to your contact number.

Also, mention your Email ID in the contact info of your profile for quick and direct communication from other professionals or recruiters who are keen on your profile.

Your profile summary should give an idea about your Aim, Vision, and Goal which generates curiosity among professionals inside or outside your Network. To make it simple, your summary should be like your story.

Make sure your Profile is 100% complete - It can be seen through profile gauge.

Mention all your relevant technical skills. Your Profile Headline should always make aware to recruiters that you are open to new opportunities.

Make sure you Like, Comment, and Share to any post related to Data Science or any technical stuff or any motivational or any informative posts, it gets you notified better.

Follow at least 5 influencers of your field, they can be Leaders, CEO’S, Trainers, and successful people.

Always monitor who has reached your profile, and always reply to them with a message

“Thank you for Viewing my profile.” Is there anything I could help you with?.

  • Step A: Your Profile Headline

    Education:

    • IBM Certified Data Scientist Looking for New Challenges/Opportunities in the field of Healthcare Analytics.
    • Note: Any Certification will add value to your profile. It can be from IBM or any MNC or any University.
    • Be domain specific (HealthCare / Retail / FMCG / Construction / Finance / Marketing / HR).
    • Mention university names like Bachelors in Engineering from JNTU / OU etc.
    • Data Science / Data Analytics Certification from City & Guilds or UTM Malaysia or any.
    • Highlight your Project at least 2-3 Domain-Specific Projects.
    • Add up your Internship experience.
  • Step B: Grow Your Network - Make sure you have a good number of connections in the Data Science Network.

    • Make a List Core / Upcoming / Emerging Companies in the space of Data Sciences / Data Analytics.
    • Target Recruiters / Talent Acquisition / HR Executives / HR Managers of Core Data Analytics Companies not limited to India but Globally. You are also free to send connection requests to Technical Leads / Directors / Managers of Data Analytics Companies.
    • Send Connections with message notes as you are looking for opportunities.
    • You have 300 Characters Limit while sending to connect, ensure to keep it short and impactful.
    • Highlight your strong skills (R, Python, AI, ML, SQL, Tableau) anything.
    • A nice professional rapport with recruiters, share your profiles directly to their Mail IDs.
  • Step C: Join Groups related to Data Sciences / Big Data / Artificial Intelligence / ML / NLP / Analytics.

    • Post some interesting Technical Blogs / Content in the groups (Gets you notified in the Group)
    • Be Active in the Group.
    • Join Group Discussions.
    • Request for Recommendations from your colleagues / Mentors / Faculty / Managers minimum 3-5 Recommendations highlighting your both Personnel/professional self.
  • Step D: Visual Appeal

    • Your display picture -should be a professional one with a nice office background.
    • Also, your LinkedIn page background should be related to Data or any technical stuff image.

“Success Mantra: Follow the above steps, and be very active on Linkedin.” Click here to learn Data Science Certification Course

Click here to learn Data Science Course, Data Science Course in Hyderabad, Data Science Course in Bangalore

                         

You may also like...

Big_Data.jpg Interview Questions
August 06, 2020

Machine learningĀ is a subset of data science which focuses mostly on building models by using the data.The models are built in asunch as way where they can learn themselves and improve efficiency,

Python.jpg Interview Questions
August 05, 2020

What are the various mathematical operations within Python? Can you explain the Python code used to perform these operations?

Machine_learning.jpg Interview Questions
July 30, 2020

Machine learningĀ is a subset of data science which focuses mostly on building models by using the data.The models are built in asunch as way where they can learn themselves and improve efficiency,

Make an Enquiry
Call Us