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If you’re graduating from college this year or just graduated, but finding it hard to land your first data science job, you’re not alone. Hear Pragyan (a data strategy consultant at Kharpann) shed some light on the topic.
It is always hard to get your first job when you’re fresh out of college with no first-hand experience to prove your skills.
And it gets even trickier when your project portfolio is just like everyone else’s since all of your peers are learning data science from a similar set of online courses. You have to understand that today there are more data science aspirants than ever before. And, as a result, employers come across tens and even hundreds of resumes every single day.
So, the question is how can you stand out from the herd?
Obviously, your skills and your experience matter but what will make you stand out, is your commitment to a particular domain of data science. You may want to work with text using Natural Language Processing, or you may want to work on Business data using Business Intelligence and you may even want to work on Image Processing and Computer Vision.
So, determining what kind of domain you’re interested in is the first step at helping yourself stand out. If you’re having a hard time doing this, I suggest you go through open-source projects in the domain and figure out what you like by trying such projects out on your own. This will help you grasp the concepts properly and build your domain-specific portfolio at the same time.
Then, the next step is to apply for jobs in a similar domain with a portfolio that best reflects your skills and interest in the domain. This will make you more noticeable from the competition since you’ve already established yourself as a specialist rather than a generalist.
Another thing you can do is participate in both online as well as offline data science competitions to get first-hand experience in working on real-world problems. This will provide you with the awareness of what problems you may face when working with data as well as how to navigate them effectively. You can even choose to team up with other aspirants and work on problems collaboratively to get an idea of what it is like to work in teams.
Having this experience is a plus-point for you as most real-world projects in data science require a lot of collaborative work. So, if you can set a clear narrative for your employer to understand that you are a self-driven specialist who thrives in a collaborative environment, then you’ll find in no time that people will actually be interested in working with you.
If you have a question of your own, feel free to comment it down.
Looking for a job in Data Science? Try Jooble-one of the biggest hiring websites in the world where there are more than 100,000+ jobs in data science from reputed organizations of all sizes.
View thousands of data science vacancies on Jooble by clicking here.
