7 Tips to Kickstart Your Freelance Data Science Career

The world is increasingly data-driven. The events of the past two years have pushed us further into a data-centric landscape, one in which Data Scientists are indispensable. As industries and businesses strive for improvements in efficiency, a Data scientist’s role in the business has become more cemented than ever.  And if you’re foraying into this field now, as a Freelance Data Scientist there are certain things that you need to keep in mind.

Possessing the necessary skills and having an exceptional data science portfolio is of utmost importance to begin a freelance data science career. But in the world of freelance, that’s rarely enough. A strong network that can help you utilize those skills is vital. The first hurdle in freelancing is always finding work, and it’s often the biggest hurdle to overcome. Building strong connections on multiple fronts is the most sure-fire way to overcome it. 

So, whether you just graduated from college or are in your last leg of a Data Science Course, you would be wondering how do I start my career in the field? Well, look no further here are 7 tips you can use to Kickstart your Career as a Freelance Data Scientist.

TIP NO. 1: CREATE A STUNNING DATA SCIENCE PORTFOLIO

This step is self-explanatory, but you might be wondering, ‘how do I create a data science portfolio when I’m still looking for work?’ The answer is simple, add any of your best projects on data science and machine learning. It can be an assignment for college or a subject that interested you, add it all to your portfolio. Additionally, you can get open-source data and play around with that! To stand out, even more, do not just stick to your strengths but also add something experimental to the mix, when creating your portfolio.

 TIP NO. 2: HAVE A  PERSONAL WEBSITE/BLOG

A website will be very telling of your skills. Incorporate work you have done previously on your website. Make sure you also write about skillsets you have accrued over time. Another great resource on your website would be, writing about the work you have done. This will help prospective clients to understand your thought process and to gauge if your work aligns with their requirements. The idea of the website is to build traction, so ensure that you link it to your social media platforms and share your favorites on Linkedin.

TIP NO. 3: NETWORKING IS YOUR FRIEND

Go to events or find communities online, these are like-minded people you can connect with and learn from. Instead of creating shallow networks, find a way to add value both ways. You can do this by working on collaborative projects with people. You can find these communities on Twitter, Quora, and even Reddit for that matter! Be proactive and strike up a conversation with people whose work you admire. Follow thought leaders and find mentorship by connecting with people on Linkedin, expressing your interest. Conferences are another good place to find a mentor!  Ask for testimonials and referrals from your network connections to build your credibility as a data science professional.

TIP NO. 4: VISUALIZING TOOLS, FOR AN IMPRESSIVE RESUME

Learning Data Visualization would make you an attractive candidate for future data science projects. Upskill by learning Power BI, Tableau, Dash, and such likes. Once, you are thorough with any of these programs, incorporate your work into your website. This would not only help potential clients see your creativity but also your ability to showcase data in comprehensive formats. While you are a data genius, the idea is for the clients to be able to understand the full scale of the work you have done, that’s when visualization comes in handy.

TIP NO. 5: KEEP PRACTISING THE FOUNDATIONAL DATA SCIENCE SKILLS

In the process of upgrading, do not let your basics get rusty. R, Python, Scala, etc., whatever may be your language of choice, keep them crystal clear. In an attempt to add to your arsenal, do not lose track of what you started with. Additionally, stripping down to the very basics, statistics and statistical modeling is still the root of all your work, remember them like the back of your hand. 

TIP NO. 6: DATA SCIENCE PROJECTS ARE THE KEY

It comes a full circle, re-iterating from point 1, find as many data science and machine learning projects or questions with open-source data and solve them. Follow them with comprehensive inferences. Additionally, work on as many collaborative projects as you can that showcase your skillsets as a data scientist. This would not only help build a portfolio but also help create references, which would help you as a freelancer.

TIP NO 7:  FIND THE RIGHT FREELANCE DATA SCIENTIST JOBS

Having followed all the above 6 tips, you are all set to look for the right freelance data science gigs based on your expertise. Make sure you deliver your projects as promised and without a glitch. It is always exciting to take on new challenges but be realistic when challenging yourself.  If you love NLP, try to find your first freelance gig on an NLP project instead of trying your hands-on niche that you do not have expertise in. One of the best ways to land your first freelance data science is to shout out to your network of friends and colleagues and let them know that you have started your data science career as a freelancer. This will help you get referrals for relevant freelance data science gigs from your network.

The next best place to find your first freelance gig as a data scientist would be to search on social media platforms like LinkedIn and Twitter where several SMB’s and startups post about their requirement for freelance data scientists. So, always keep your social media profile up-to-date and relevant to your field of work to get the right referrals and gigs.

So there you are all set to begin your data science career, all you need is hands-on experience working on real data science problems and strong foundational data science skills.

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