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How To Work As A Freelancer In Data Science

How To Work As A Freelancer In Data Science

Data science

Are you a data scientist looking to launch your freelance career? If you are a beginner, taking on freelance work on data-related projects will not only help you build your portfolio but also help strengthen your data science skills.

From how to market yourself to get clients, to choosing the right tools and platform, the following tips will help you kickstart your journey in this space:-

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Build Your Brand

When starting off as a freelancer in data science, the first step should be to prioritise personal branding. While being active on your social media platforms like LinkedIn and Twitter would help, do not rely on these channels to generate leads for you.

Instead, create a comprehensive profile on platforms like GitHub, or even Medium to demonstrate your data science capabilities. A good practice would be to be meticulous with each project – make ample use of data visualisation for better illustrations. You should also include pieces you may have written on data science and machine learning. It not only demonstrates your prowess as an aspiring – or practised – data scientist, but also displays your commitment in this field. 

A big plus towards building your brand would be to speak at conferences. This not only establishes you as an expert but also provides a medium to network with like-minded people. Also, engage in chat forums to inquire about organisations or clients seeking freelancers. Responding to questions on Stack Overflow and Quora will also help get you noticed.

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Identify The Right Platform

When signing up on freelancing sites, choose the one that is user-friendly – and free. Although there are multiple websites you can turn to, both Upwork and Toptal are good options. These offer tons of tools and features to deliver your projects successfully. This includes real-time chatting with clients, timesheets, as well as for analytics.

Data Science Stack Exchange and Kaggle are excellent options as well. While the former comes with a Q&A chat forum, the latter hosts data science competitions.

Find Your Niche In Data Science

Data Science is a broad, interdisciplinary field, and that necessitates narrowing down your skill sets to find relevant applications in businesses. Moreover, to make your profile more marketable, you should draft a plan that is committed to solving specific problems of a smaller subset of people.

In other words, the more focused you are, the more chances of acquiring rewarding projects. The idea is that by tailoring your offering to a specific set of people, you are amplifying your chances of acquiring projects by delivering unique solutions.

You can still diversify your skillset in the future as you build your expertise in the field. But for your first profile, it is recommended that you choose the area of data science you are most comfortable with, rather than chasing the next popular space.

Understand Your Clients

As a freelance data scientist, you will most likely liaise with the CEOs or CTOs or software engineering managers of organisations. Understand them carefully and approach each of them in the right manner.

For instance, CEOs are constantly seeking the best ways to stay ahead in a competitive marketplace. In most cases, they may not understand the value you bring if you know particular tools. All they are looking for are ways to improve the metrics their performance is judged by. On the other hand, CTOs and Software Managers will be looking for specific answers to specific questions.

Set Your Net Worth

Most freelancers tend to charge too little – do not do that. You should be adequately compensated for your work. The demand for data scientists will only go up, so there would be plenty of work available.

While a postgraduate degree surely qualifies you for profitable gigs, it is still essential to building up your arsenal of skills sets. While you can read about basic skills here, it will be good to familiarise yourself with additional tools such as Scala, Spark and Amazon Elastic Mapreduce.

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