Data science is an interlinked field that broadly deals with methods, processes, analysis, complex algorithms. Data scientists use all of those to extract insights, conclusions from rough and often unstructured data to help companies, governments, sports leagues, medical giants to predict outcomes. They also closely deal with big data and data mining. We are living in a world that is experiencing a constant paradigm shift because of technology. And by large, it is driven by data. Data science, therefore, has become a career that has attracted skilled talent like never before. With its set of stimulating challenges, solutions, and prognostications, data science also offers lucrative salaries to the professionals. Being involved with a multinational corporation as a data scientist has its perks and benefits. You undoubtedly get to work on blue-chip projects with coveted companies, however, with time, it can also get less challenging and predictable. In this blog let’s find out how you can begin your journey as a freelance data scientist.
How to Start Your Journey as a Freelance Data Scientist?
Let’s be honest, many data scientists have already thought of working independently and start as a solopreneur. Just like every other line of business, even data science has no dearth of experts. To be valued as a freelance data scientist, you would have to devise a strategy and think like an entrepreneur. With a bit of thought, perseverance, and research, you can cut the competition and become a much sought out freelance data scientist. Keep these hacks in mind for the same:
1. Maintain a Portfolio
Your portfolio can make and break your freelance dream! Showcase all your important projects there, references/recommendations from your clients and also make sure to reveal all the practical outcomes of your deliverables. A great portfolio is a foundation for getting serious clients who believe in your abilities.
2. Know Your Market
Before taking the plunge as a freelance data scientist, study the market. Lookup for the industries that are trending and carefully make a list of startups, small and medium businesses, corporations that you could offer your services to!
3. Create a Fund
As a freelancer, start putting some funds on a monthly basis aside for expanding your business. That chunk of saving will be your cushion when there are any industry transformations or emergencies. Also, in case you need to hire interns for a demanding project then this fund can come to your aid.
Data science events and even start-up or small business meet-ups are a great way of interacting with founders and new people. Try to genuinely hear them out and offer assistance to them in a way you can and you never know, you might just get your next client from that one random meet-up! Additionally, online portals like Meetup.com, LinkedIn offer a great way to interact with other freelance data scientists out there and also pitch to companies via InMail or connection requests.
While word of mouth would surely get you a few sets of clients, never forget that cold pitching would be an integral part of your business development. Create a database of companies, business heads that you could reach to pitch your services as a freelance data scientist. Use all those details to send cold emails or reach out through calls.
6. Be Visible
Create an active social media presence on LinkedIn and Twitter to network with professionals and businesses. Also, lead sites like Upwork, Fiverr, Toptal, AngelList can be used to reach international and local businesses. So, make sure you create profiles on them! Also, get active on community platforms like Gitter, CrowdAnalytix, Data Science Central, KDNuggets, Data Science Stack Exchange, FounderDating.
7. Manage Time
As a freelancer, you would be your Boss. Create a schedule for yourself throughout the week and by large for the month. Have a calendar handy and ensure that you are following proper timelines to start and finish the projects.
8. Be the Jack of All the Trades
You are great at data science. However, to break through as a freelancer, you would have to master accounting, writing, business development, finance, marketing, public relations, management, and many other things. Ensure that you have an understanding of all of them!
At the same time, having the core knowledge about data science is hands-down the most valuable skill that you would take to the table. So, along with augmenting your skill set, make sure to always know the fundamentals and innovations of data science.
9. Keep Learning
Last but not the last, if you start working independently, you would have to know more than most of your peers. Stay ahead of the curve by reading as many books, blogs as you can on data science and even businesses, startups. And keep listening to insightful podcasts like Banana Data, Data Skeptic, Data Framed, Data Stories, and Linear Digressions et al. Engage in fruitful discussions with the community of data scientists and keep brushing your knowledge.
Why Switch as a Freelance Data Scientist?
For the sake of more freedom, challenges and being one’s Boss, many talented professionals have plunged to work as a freelance data scientist. By doing so, they have not only had more say on the projects that they want to work on but also more work-life balance. If you like to solve problems, have relevant expertise in terms of business, technology, learnability and an inclination towards computer science, maths, programming languages then you may consider becoming a freelance data scientist. Most importantly, by being a freelancer in the field of data science, you can choose to work as per your convenience and create a lifestyle of your choice.
Contemplating a Career as a Freelance Data Scientist
Overall, there is a perception that it is important to have at least a few years of experience as an in-house data scientist to carve a niche as a freelance data scientist. However, that’s just a relative opinion. Because many talented data enthusiasts have become freelance data scientist right after college or have started out even while studying.
Many companies that you would approach as a freelancer or vice versa, would check your background, your expertise. If you have worked as a full-time employee with a few great companies beforehand, learned on the go and dealt with a plethora of challenging projects then it would work in your favour. But at the same time, leading those data science societies, helping startups, creating a strong profile, upskilling yourselves would put you in the same league as that of professionals if you do not give up! Therefore, never let the idea of not working full-time stop you from starting your journey as a freelancer.
There is no rule about starting out as a freelance data scientist. Starting out as a freelancer is more of a mindset, entrepreneurship and business game than anything else. To beat the odds, read up about data science as much as you can whenever you get some time and start executing those ideas.
In a Nutshell
Try to walk extra miles for yourself, take relevant courses on data science with Springboard to remain in sync with the trends of the industry and you would be able to make a successful living as a freelance data scientist. So, while you are actively searching for data scientist jobs, think about researching for a freelance data scientist salary as well because you may become your boss sooner rather than later!