How to Become a Freelance Data Scientist?

The freelance and consultant market has been experiencing massive expansion considerably over the past decade. Websites like LinkedIn has seen exponential growth (of 43 percent) in the number of freelancers over the last five years. The trend has also witnessed that companies prefer to hire independent contractors and freelancers over full-time employees. Even in the vertical of data science, freelancers are doing wonders. So, now you can choose a freelance career and become a data scientist. This article will guide you on how to become a freelance data scientist and the way to proceed.

Data Science and Freelancing – How to Get Started? 

Data Science has become an ever-expanding domain. Most organizations rely on data analysis and its prediction techniques for vital information and exerting critical business decisions. Among all the different roles of data science, data scientists are in high demand. Although, it is a fact that data analysis is best carried out by those who understand the work and goals of the organization. But the trend changed. Lots of freelancers and consultants are actively into data science and catering their services to the organization. The appeal of working with data and algorithms while maintaining a flexible work schedule with high pay brings in a significant headcount of freelancers to the market.

Steps to Become a Freelance Data Scientist

Furthermore, LinkedIn is rolling out new features to help freelancers find work. Because of such evolution on various platforms, now is the best time to kick-start your career as a freelance data scientist. Here are some of the essential steps you have to keep in mind while starting your freelance career. These points will help you enhance your current strategy.

·        Build your Presence: The very initial process to start freelancing is to establish and curate a robust online presence. For this, you need to create your website, LinkedIn page, and profiles in other job listing sites. Use those pages and profiles to exhibit your skills. Prepare a portfolio mentioning your relevant work experience and market yourself to the best foot forward. Make sure your work details are crisp and easy to understand. Also, remember to make the site easy to navigate. Otherwise, people might click away. You may also use other platforms like opening an account on Google my Business listing. In that, you can put your relevant details and connect your website. Through this platform, companies can get a quick search for data scientist freelancers. It is essential to keep updating all the profiles and use those online marketplaces to advertise yourself as a freelancer.

·        Know your customer: In every organization, only a handful of people have the power to hire data scientist freelancers. They are the founders, co-founders, executive head, CTOs, Sr. software manager, and some other ML or R&D department head. You can target these people to showcase your skills and data science experience. It is because these people are your customers who can hire you and give you long-term data science projects.

·        Develop New Data Science Skills: Data science is an ever-changing domain. New algorithms and techniques come into existence every moment. That is where you must keep up with the evolving pace and the demand for the job. Turning to online courses is also a clever choice when you don’t have any specific skills. You should also include your data science certificates and certifications in your profile. It will boost your appeal and eligibility for the freelance data science-related job.

·        Pick your Niche: Data science is a vast domain. Every data scientist puts their best starting from a rudimentary data warehouse, implementing regression analysis from scratch, and to training a complex CNN. But working on a wide radius of the domain makes your freelance career indistinguishable. Therefore, to reach your customers, you need to be specific with the niche. Apart from that, prepare a marketing plan dedicated to your client’s problems. It makes your goals plain and apparent.

·        Work across Industries: Data science professionals and data scientists are in enough need because most organizations rely on data-driven decisions. It is another benefit of this job. Tech jobs like data scientists are in great demand across industries, irrespective of the domain in which the firm works. For instance, healthcare firms, travel agencies, BFSI sectors, biotech firms, etc., leverage data scientists for monitoring sensitive information and extract valuable insights from data. This way, freelance data scientists can work in a diverse set of industries. It eventually increases their rate of getting more potential clients. But as a freelancer, you have to be specific about the services and the type of companies you want to serve comfortably.

·        Use Online Platforms and Resources: Since you are comfortable scrounging for data science courses, you can further leap and look for freelance platforms. There are online platforms, resources, and websites that can connect you with professionals in need to hire data scientists. Through those platforms, you can take off as a freelancer.

o   Upwork: It is a freelance-specific platform where you can get potential customers. Recently, Upwork has gone through a merger with the well-known freelance platform Elance-oDesk. This merger made the firm a giant in the industry of freelance. Upwork is catering to 1,900+ job listings in the field of data science.

o   Toptal: This popular freelance platform helps connect businesses with freelancers like data scientists, data engineers, software engineers, designers, content curators, etc. It will help you connect to potential clients without much hassle.

o   Kaggle: Kaggle is another all-in-one platform where you can learn, collaborate, and find a community of data-oriented professionals and curators. Through this platform, you can create your client base.

According to the report of Glassdoor, data scientists can make roughly $110,000 annually. As a freelancer, you might start with a little less than the average. But finding the right client and understanding the proper rate of your service is also critical. You have to research the market rate while your hours will be up to you. You can compile your overall salary to an hourly rate. On average, a freelance data scientist can fix a rate tag of $45 to $50 per hour. Always remember not to sell yourself short — recognize your worth.

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