Becoming a freelance data scientist or data analyst can be very rewarding.
If you are successful, this is an opportunity to earn more, improve your work-life balance,
and be your own boss.
However, it is also an entrepreneurial journey.
The competition is fierce with other individuals around the world who have chosen the same
path as you.
It isn’t easy, especially at the beginning…
So, in this video, we’ll try to provide some genuine advice on how to get started
as a successful freelance data scientist.
Our team has spent the past few years working with freelancers, which puts us in a good
position to share some of the best practices in the field that separate top performers
from those who haven’t managed to make a name for themselves yet.
Let’s dive in!
Before you begin your journey into freelancing, you need to consider your current situation.
For example, are you currently in full-time employment?
One of the first choices that you need to make is whether to keep your traditional job
or to freelance around the clock.
Both options have their pros and cons, and the optimal solution depends on your personal
circumstances.
However, quitting your current job to pursue freelancing full-time isn’t the only possible
option.
Especially in the beginning, you can have a transition period during which you keep
your 9-to-5, but also do some freelancing gigs on the side.
This approach has a couple of significant advantages:
First, you can test the waters and see for yourself what does it mean to freelance.
In fact, it is quite different than being a regular employee – as a freelancer, you
have to be able to work autonomously and carry out a specific type of project work from end-to-end
with limited to no management.
Second, keeping your full-time employment for the moment allows you to gain some traction
on freelancing platforms like Upwork and Toptal.
Having said that, let’s talk about freelance platforms, shall we?
One of the best and most consistent ways to find freelance work is to build a successful
profile on a globally renowned platform.
Websites like Upwork, Toptal, AngelList, and others can connect you with thousands of business
owners around the world.
Many of them are willing to pay top dollar for your services.
That being said, selecting the right platform is a very important decision.
For example, if you opt for Fiverr, clients might expect you to deliver a bargain deal,
which is far from ideal.
Therefore, Toptal and Upwork are probably the 2 best options.
There is a much higher volume of business on Upwork and freelancers tend to charge from
30 to a few hundred dollars per hour (for machine learning projects).
Toptal, on the other hand, brings less deal flow, but might introduce you to high-end
corporate clients that will stick with you in the long term.
While it makes sense to be listed on multiple platforms, perhaps it is optimal to focus
on only one of them.
Make sure all your marketing materials point to the same platform – this is where you
want to build your following and move up the rankings.
Essentially, splitting reviews isn’t a good practice.
Platform economics work in the following way: Buyers will search for top-rated talent with
significant social proof.
They will also look at your previous projects and try to assess whether you’re the right
person for their current needs.
Someone who has previous work history related to data cleaning projects only will have a
hard time getting model building tasks.
So, you have to be mindful of: 1.
How many reviews and hours you have billed 2.
The type of projects you accept to work on 3.
The prices you’ve listed for your services 4.
How structured and well-written your description is – please try to be very specific and
put emphasis on the type of projects you’ve worked on, as well as the results that you’ve
delivered; include as many specific KPIs and measures as possible
5. Make sure you have an excellent portfolio with data projects that support the services
you’re offering A very important question to ask is how much
you should charge for if you’re just getting started.
Don’t fall into the trap of selling yourself short.
Instead, start with a higher list price, then bid on projects offered on the platform at
a significant discount.
This will increase the perceived value clients have of your services and allow you to gradually
decrease discounts as you accumulate social proof.
And if you’re qualified, don’t hesitate to charge premium prices!
Similarly to social proof, the price you’ve set for your services speaks of the quality
of your work.
Premium clients (who are the best customers) might be put off by low prices.
Ok, great!
Is there something else you can do to get things moving in the right direction?
Marketing is always helpful – but especially crucial in the beginning.
Make sure to put in the effort to get noticed and win your first customers.
How can you do that?
Remember, it isn’t easy to get your first few roles by relying on freelance platforms
alone.
Competition is fierce, and there will be many other applicants bidding for the same job.
Due to this, it is important to continue promoting your work off-platform and building a social
presence.
Whenever you post about a new project you created, include a link to your profile on
the freelancing platform of your choice.
Pin it to your LinkedIn profile so that every time you connect with someone, they can see
the services you offer.
Moreover, you can start by writing data-related tutorials on platforms like LinkedIn Pulse,
Towards Data Science, KdNuggets, and 365 Data Science.
If video creation is a viable option for you, then starting your own YouTube channel can
be very helpful as well.
Finally, depending on your skills, you might want to get into Kaggle competitions.
The more people that notice you at the beginning, the better your chances are of success.
What kind of data projects can you expect when you are a freelance data scientist or
data analyst?
For starters, as a freelance data scientist, you can build models for organizations on
a one-off basis.
There are many companies out there that don’t require an entire data science team.
Instead, they just need someone who can build machine learning models to solve specific
problems using the data they have available.
In the same way, you can be asked to use a company’s data to build a KPI dashboard
they can use to monitor performance over time.
One of the most frequent types of requests for freelance data scientists is related to
cleaning raw data.
Many organizations have accumulated millions of data points, however, they are unrefined
and cannot be used to glean meaningful insights until processed.
This is where your services can come in handy!
Other popular types of work include web scraping and formulating and setting up A/B tests.
Plus, as we’ve already mentioned, you can create tutorials and useful guides.
There’s an enormous amount of companies looking for technical writers for their blogs.
Keep in mind, this gig is suitable for junior candidates.
It really depends.
With an abundance of projects that companies are looking to outsource, it is pretty much
up to your current skill set and abilities when deciding which is the optimal work for
you.
If you are a beginner looking to learn the skills to become a freelance data scientist,
the 365 Data Science Program offers self-paced courses led by renowned industry experts.
Starting from the very basics all the way to advanced specialization, you will learn
by doing with a myriad of practical exercises and real-world business cases.
This is the one-stop solution you need to start your data career.
If you’ve enjoyed this video, make sure to subscribe to our channel for more insightful
content.
And don’t forget to spread the word so more data science enthusiasts know about all the
exciting opportunities that are out there!