5 Reasons Why Every Data Scientist Should Start Consider Freelancing

Discover how freelancing can accelerate your data science career with insights into problem-solving, skill development, flexibility, and financial freedom. Learn why every data scientist should consider freelancing for professional growth and security.

Feeling Stuck in Your Data Science Career? Here’s Why Freelancing Can Help

The struggle of not feeling fulfilled in data science

Are you feeling stuck? You got the degree. You got the job. You're working in data science. You're killing it. But for some reason, you don't feel like you're progressing in life. You're not growing. You're not developing the skills that you want to develop or maybe you haven't even gotten the job yet.

Applying for jobs but feeling unsure about the future?

You're desperately applying for jobs. You're getting scared all the tech companies are laying people off. What am I supposed to do about this? How am I supposed to get a data science child? But just a bachelor's degree with my Master's Degree with my PhD. Even if you resonated with any of these random points. I just spat out at you then this article is for you.

Hey everyone. I'm Icoversai and as someone who has worked in data science as both a freelancer and a full-timer. I just wanted to share a little bit of my experience with those pondering and reflecting on their data science journey and trying to figure out where they want to go with it toward that end.

Reason 1: Freelancing Offers Exposure to New Problems in Data Science

How freelancing allows you to apply techniques across different industries

In this article I'm going to break down five reasons, why every data scientist should at least consider freelancing? So in my view, these points are beneficial to anyone in data science, but perhaps especially. So for those just getting started in my personal experience freelancing accelerated my development as a data scientist and it played a big part in helping me and get my current full-time role as a data scientist.

If your goal isn't to get a full-time gig at a company freelancing can serve as a main source of income or even give you insights into different industries that might help you develop a new business or a minimum-viable product.

So if you like this content and want to see more about data science productivity and entrepreneurship, please consider subscribing that's a great no-cost way you can support me in all the articles that I made last year. So the Website algorithm will know that you want to see this face on your computer screen and with that, let's get into the Five Points okay.

The power of logistic regression across various contexts

The first reason, why every data scientist should at least consider freelancing is to work on new problems? One of the greatest powers of data science that I personally just love so much is that data science is so often context-agnostic. So what do I mean by that? Basically, all I mean is you can take one method, one Technique, One Piece of code and apply it to multiple different use cases. So like a very simple. One is logistic regression, you can use logistic regression to solve binary classification problems which comes up in credit risk modeling.

Will the person, I'm giving a loan to pay me back or analyzing customer retention? What's the probability that our customers will continue our services next month or even marketing analytics? What's the probability that a user will buy our product after they read our ad? So these are completely different contexts we're talking about credit risk and financial services lifetime customer value with retention analysis. Then we're talking about ads and marketing with that last Point completely different context. But you can use a single data science approach to solve all of these problems and these are just three off the top of my head.

There are countless use cases and applications for logistic regression or any common data science approach. So all that to say, when it comes to freelancing, you have the opportunity to use this basic toolkit in a wide range of contexts. When I was freelancing, I was working as a graduate research assistant in the physics department, but through my freelance work, I gained exposure to different fields.

Expanding your skill set with diverse real-world challenges

So one example was trying to classify sepsis sub-phenotype. Basically subtypes of sepsis using unsupervised machine learning techniques that I've used in countless other contexts. So that's one thing to consider when thinking about freelancing and data science. You have the opportunity to work on different problems leveraging your experience and the skills that you've acquired in new contexts and it kind of enriches your understanding of those tools. So every time you use a technique in a different context. It helps you build an intuition of what else you can use that same method.

Reason 2: Developing Essential Soft Skills through Freelancing

Networking, cold emailing, and the art of client communication

So reason number two is developing soft skills. When you're freelancing, you're really on your own. You have to figure out, how to put yourself out. There, how to get clients and how to communicate with a diverse set of people? So when you're freelancing, you're trying to find gigs. You often have to network. You have to talk to people. You have to connect with people and this really forces you to develop your soft skills.

You know sending out cold messages, email etiquette talking to people at networking events reaching out to people on LinkedIn responding to potential clients. Reaching out to you because they see some work that you've done or they came across your profile on some freelancing website like Upwork or Fiverr.

The importance of interpersonal skills in the freelance world

All these interactions all these reps really allow you to develop these soft skills that you may just not have as much opportunity to develop in a full-time role, where the work is more delegated to you and is more stable and you're typically interacting with the same handful of people constantly as opposed to in a freelance role. You're interacting with new people and brushing up on those skills.

Reason 3: Fine-Tuning Your Resume and Pitch for Success

How freelancing gives faster feedback than traditional job applications

The third reason is fine-tuning your pitch and this has some overlap with the second reason. It comes down to your ability to communicate and connect with people, but fine-tuning your pitch is really about selling yourself. What I mean by this is fine-tuning your resume, your cover letter or proposals, and your interview skills. So this is another area where full-time roles and freelance gigs have a big difference. It ultimately just comes down to timeliness.

So for the full-time role. You know, you submit your resume and cover letter. You spend all this time on it but it's not uncommon to not hear back from that application for weeks or even months sometimes. So it's really hard to kind of gauge how effective your resume and cover letter were and conveying your skill set and experience. But on the flip side in freelancing, the time scale is just much faster, if you apply to a gig.

Let's say on a site like Upwork the feedback is typically much quicker if someone wants to work with you. You will a lot of times hear from them within a few days. If you don't hear back from them in a few days that probably means they're moving forward without the candidates or the jobs no longer relevant or something like that. So ultimately what this means is in freelancing as opposed to full-time roles. You really can get a lot of reps in on your resume and cover letter and get much faster feedback.

Mastering your personal brand through constant iteration

So what this allows you to do is fine-tune your resume and cover letter to convey your skills and experience more effectively. This is something I definitely benefited from, so I was freelancing in grad school. So constantly fine-tuning my resume and my cover letter and then eventually, when I graduated and decided to apply for a full-time role, my resume and cover letter were in a pretty good spot. I could just leverage what I learned from freelancing to apply to the full-time gig.

I would say to anyone trying to break into data science. You know you just graduated or you're about to graduate. I would recommend freelancing even if you don't get any gigs and don't get any work through it. At least, if you get these reps you get to fine-tune your resume and your cover letter and hopefully your interview skills through chatting with potential clients. You can leverage this experience in these reps and the feedback for applying to a full-time gig.

Overall the skill set of selling yourself being able to communicate your skill set and how your experience and skills are relevant to solving other people's problems is a very valuable skill set to have and essentially being able to sell yourself. Your ideas are something that will be valuable in whatever context you find yourself.

Reason 4: Enjoy Greater Flexibility and Autonomy with Freelancing

Choosing your projects, clients, and workload as a freelancer

Reason, number four is flexibility and autonomy. So this is one of the greatest benefits of freelancing and I feel one of the main reasons, why people are so attracted to it and freelancing? You essentially choose what you work on? Because you choose the clients that you work with. Moreover, freelancing gigs are typically on a much shorter time scale than full-time roles. So you could be working with a client on a month-by-month basis and it could be going great for six months, but then at a certain point, the work May no longer be relevant or getting overloaded on contracts with a handful of other clients.

The freedom to work from anywhere and live the digital nomad lifestyle

Then you have the option and opportunity to reduce your workload or refocus your efforts toward a specific type of work and also you don't just get to choose, what you work on? But you typically get to choose where you work? How do you work? When you work this is something that a lot of people have value in people. Who greatly values their autonomy?

Their flexibility, their freedom, you know maybe, they don't want to be bound to a certain city. They want to be able to travel and you know this was something that got big during covid. You know people were getting gigs online or during remote work. They were living for months in different countries. You know living in Europe or South America or Asia or something like that. So for people whose lifestyle is appealing to them, freelancing is a great option, okay.

Reason 5: Building a Valuable Network as a Data Science Freelancer

Connecting with professionals from diverse industries

The fifth reason is networking. So I kind of touched on this before, but here when I'm specifically talking about building new relationships and new connections. So through my freelancing, I've met a wide range of people that has given me insight into Worlds that I didn't even know existed. I've worked with medical doctors clinicians people working in the Special Forces military police officers business people.

Learning from different backgrounds to broaden your perspective

You know so many different walks of life and backgrounds and has really enriched my own experience and my understanding of the world. I find a lot of value in relationships and learning from people is something. I give a lot of weight to, so this is one aspect of freelancing that I really enjoy, okay.

Bonus Tip 1: Freelancing Can Be More Lucrative Than Full-Time Roles

The financial benefits of freelancing compared to salaried positions

If those five reasons were not enough to make you consider freelancing in data science I've got two bonus tips to share. So the first bonus tip is money. So even if you don't really care about developing your technical skills expanding, your experience and Horizons, developing your soft skills, and building new relationships. What else did I talk about fine-tuning?

Your pitches and your ability to sell yourself. All these different reasons, you could always just do it for the money and most of the time freelancing gigs are much more lucrative than full-time roles.

Why freelancing offers financial flexibility for data scientists

So just speaking from my personal experience, before I entered into my current full-time role. I had two offers on the table. I had my current role and I had a essentially a contractor role which could have been full-time and just comparing the pay of the two roles. The contract rule paid almost twice as much as my full-time gig. I would say 80 percent. Paid about 80 percent more than my full-time gig which is a lot of money.

I'm just saying that to give you an idea of how much more you could get as a freelancer as opposed to a full-time role and to those who are saying like, oh! If freelancing is so great why didn't you take that, why don't you take the money and that was just a personal decision for me. When I graduated, I'd done the freelance stuff. I'd worked in research, but I never worked at a large company as part of like a big data science team. The biggest team, I had worked with was my research team which was about 12 people.

I work on a data science and analytics team that I want to say like 100 people. If not more and so for me the reason, I went with the full-time role is because it was a new experience for me. It was also the opportunity to learn from other data scientists and data analysts who have been working in the field much longer than I have.

The last thing, I'll say about the money is that you know the great thing about freelance is that you can customize the freelance workload. So you can definitely be a full-time freelancer and reap all the benefits there. But, if you're just trying to make some extra cash on the side and you have a full-time role. You can probably just pick up one contract every. So often if you just want to make some extra cash on the side.

Bonus Tip 2: Freelancing Gives You Career Options and Stability

How freelancing can serve as a safety net during uncertain times

The second bonus tip is that freelancing gives you options. If you have freelancing experience or you've done it in the past. So say you're working full time and you want to make some extra cash, you can always just go to freelancing or kind of given all the recent Tech layoffs. It's kind of a scary thing, you could just wake up one day and your full-time employer says we don't need you anymore or We don't see the value in data science anymore.

Balancing full-time work and freelance gigs for extra income

They lay you off now, What are you going to do well? If you're freelancing on the side or a freelancer in the past, you have an immediate thing.

Conclusion: Why Every Data Scientist Should At Least Consider Freelancing

Empower Your Career and Future with Freelancing in Data Science

So in this article, I give you five reasons why every data scientist should at least consider freelancing with two additional bonus tips. So if you enjoyed this content you want to read more take a look at the blog associated with this article published in Towards Data Science on Medium.

5 Reasons Why Every Data Scientist Should Start Consider Freelancing - icoversai

Table of Contents: