Welcome to Episode 25 of Data Science and AI Weekly!
Are you looking to become a Freelance Data Scientist?
Here are a few tips to help you get started and succeed as a freelance Data Scientist.
You can follow the podcast here:
TIME-STAMPED SHOW NOTES:
[00:07] Welcome to Episode 25!
[00:35] Milestone Episode
[00:45] Topic of Discussion: How to become a freelance Data Scientist?
[01:14] Part-Time Vs. Full Time
[01:39] Requisites of a good Freelance Data Scientist
[03:32] Identify a niche for yourself!
[04:07] Where to find freelance projects? How much should I charge?
[05:04] Wrap up!
[05:57] Learn more about Data Science at www.accredian.com
Hi, everyone, welcome to Episode 25th of Data Science and AI Weekly.
First of all, if you have not subscribed to our YouTube channel, make sure that you do that so that you get the latest notifications from this amazing podcast that we do twice a week. At least we try to ensure that it gets launched twice a week for sure.
This is Data Science and AI Weekly, Episode 25th and we are hitting a milestone with this episode. And I hope you have loved the series so far because I have totally enjoyed doing them.
So in this episode, we have a very interesting topic that some of you have been requesting for and in fact, I clearly remember I got an email also sometime back, couple of weeks back that Manav, can you do an episode on how to become a freelance Data Scientist.
So let’s get started with this episode. Now the first thing that you need to do if you’re wanting to become a freelance Data Scientist is you need to, first of all, ask these questions that whether you want to become a freelance Data Science scientist immediately, or whether you want to become a freelance Data Scientist while continuing with your current job, you want to take this on the side.
So there are two approaches and both approaches have their own pros and cons.
The second thing, what you need to ask is that if you’re looking to become a freelance Data Scientist, would you have three of these things?
Number one, do you have the requisite skills in Data Science Machine Learning to advise a particular client.
Number two is do you have a portfolio to give someone the confidence that you can take up those problems?
Also, Do you have any credible work of similar industry that you’re interested in taking projects from?
For example, let’s say that you are interested right now, you decided that instead of taking any kind of projects, I would want to, let’s say, take up projects from BFSI, right?
So if you have worked on the BFSI projects in the past or during your program itself on data sets, then it would certainly help you because you would be more closely in touch with BFSI problems.
So these are the three parameters that you should be looking at before you’re looking to take up Data Science projects.
Now, this is the first thing.
The second thing that you should be looking at is that are you in a position to ask questions to a client on a very high level. For example, sometimes the client might not even know whether they require Data Science or not. Right. So that’s again, another problem.
Sometimes the client might want you to do a very specific kind of task in a Data Science project, for example, there are enough tasks out there on data cleaning, right. So whether you would want to do data cleaning, which I think there is no harm in doing that, because it gives you a certain amount of experience.
So you would want to identify those niches for yourself, where you can project that this is the kind of work that I’m looking to do. And the reason why you would want to do that as Data Scientist in itself is a very, very broad area.
The more specific you are, the more clear you will be with what you want to do, what you want to achieve. And the more clear the client will also be in terms of what they should approach you for, right.
And once you have two or three of these clients, right, then you can take more, more clients after that.
Now the question that you would have is, where do I find these freelance projects from? And how much should I charge for them?
My first advice always is that when you’re getting started in the field, do not worry a lot about how much should you be charging. Charge as nominal rates as possible.
In fact, do it for free for some of the people. Say that I’ll do it for free or at a minimal cost. The reason is that people would want to give you a chance right now you’re not looking for money, what you would want is some exposure.
That’s one. Second is where do I look for projects, there are enough freelancing websites. Just do a Google search: Data Science freelance projects, and you will be able to get some of the links.
Go through these links and try to understand what are the requirements of the projects and then you will be able to understand what should be your next steps.
So just to summarize, first of all, identify whether you want to do freelancing full time or whether you would want to continue with your day job.
After that, identify your niche.
And third is start by researching a little bit on the kinds of opportunities available on the net and you can do it by googling it, and then study them and accordingly find the right fit for you.
Right, so those are my tips for you to being successful as a freelance Data Scientist, it’s a fantastic thing to do. And I’m, in fact very, very bullish on freelancing Data Science as an opportunity because a lot of companies still can’t hire full-time Data Scientists or might not have enough work for full-time Data Scientists.
And this is something that you should definitely look towards.
So I hope you loved this episode, which is Episode 25th. And if you did, leave a comment. Like this video, share with your friends and see you in another episode of this amazing video podcast.
