Spoiler alert — Yes, but there’s a catch. Here’s my experience after 2.5 years.
There have never been more job openings for data science positions, but yet, it’s never been harder to get hired as a data scientist.
Why? The answer is simple — smaller companies usually don’t need an entire data science department, so they end up hiring a couple of seniors. That sucks for you. On the other hand, you likely won’t get hired by big corporations without experience before hell freezes over.
There’s something you can do to increase your chances or even to stop looking for data science job postings altogether. Heck, that something landed me a couple of dozens of job offers in the last 2.5 years. The best part is — the same can happen to you. That something is starting a data science blog.
Don’t feel like reading? Watch my video instead?
Why You Should Start a Blog as a Data Scientist
I could talk about this for hours, but the reasoning boils down to three points. I’m sure you’re aware of all of them, so consider this section as an optional recap.
It’s the fastest way to learn
So, you’ve learned how PCA works. Can you explain it to a 10-year-old? Can you ditch the fancy eigenvalue and matrix terminology without losing the core idea? If so, you truly do understand the topic. If not, go back to the drawing board.
Writing about complex topics, and hence, teaching them, without big words is a challenging task at first. After all, a lot of them are here just to make whoever wrote the book sound smarter. In reality, unnecessarily overcomplicating things makes you sound like a douche. Use small, easy-to-digest words. Your readers will love it, as most of them don’t hold advanced degrees in quantitative fields.
Writing about complex topics in easy-to-understand language will also skyrocket your level of understanding.
It’s an amazing way to build a reputation
I would never want to be an IT recruiter with the task of filtering hundreds of job applicants. It’s a horrible place to be. Making matters worse, there’s a limited time window to separate good matches from the background noise.
Here’s a rule of thumb — if you don’t stand out, you get filtered out.
Linking to your data science blog in your resume can make a world of a difference. Most of the applicants won’t have a personal data science blog, so it might be your golden ticket.
It shows your thought process
Distilling complex topics into 5-minute articles is a huge accomplishment. The benefits don’t stop here. Your articles also showcase your thought process, which signals to potential employers how you think and approach the challenges of a modern-day data scientist.
It shows you’ve taken time to understand the topic fully, and that you’re not rushing from one thing to the other. It doesn’t sound like much, but being able to focus on one thing is somewhat rare in today’s world ruled by a short attention span.
My Results After ~2.5 Years of Blogging About Data Science
I was working full-time when I started a data science blog. I’m still working at that same job until the end of the year. Ultimately, I decided to quit because blogging about data science makes me 2–3x more money than working as a data scientist. It also slashes my work hours significantly.
Blogging about data science resulted in dozens of job offers in two categories — data science and technical writing. Both are good, but the offers differ significantly between categories. I’ll do my best to explain both next.
Data science blog ➡️ Data science job offers
I got 4–5 job offers for full-time data science positions just based on my data science blog. But here’s the harsh reality — these occurred only after I put the initial effort into the blog. Starting a data science blog is one thing, but being consistent with it is something else. It took me about 1.5 years to get the first job offer.
And I think it’s fair — no one takes you and your little blog seriously if you don’t. There’s no better way to show you mean business than by sticking to it without seeing any results.
Some job offers I received were completely remote, but I decided to pass on all of them. After all, it’s just trading one full-time job for the other, which makes no sense if you’re happy where you are. Also, most of them were in the area of work I couldn’t care less about, like corporate finance. I’d rather set myself on fire.
Data science blog ➡️ Technical writer job offers
I had a couple of dozen offers for technical writing positions, either on a freelance, part-time, or full-time basis. I got the first technical writing offer much sooner than the first data science offer. I don’t think my writing is spectacular, but companies need someone to write content about their product or service. If they host their own blog, and if the product leaves some sort of a wow factor on me, I generally agree.
I like these offers better for multiple reasons. The job is much simpler, comes with less red tape (if any), is completely remote, and I can set my work hours. It’s a win-win, as a company gets the exposure they aimed for, and I can write while riding a bike in the mountains.
Because I’ve somewhat built a reputation online, I can charge a premium for my writing service. Usually, I end up making my country’s average salary in about 2–3 workdays. You can do the same.
Just keep in mind — finding good-quality clients is difficult, and it’s even more challenging to find clients that have consistent work for you. I have a couple that need an article per week, but these account for around 5% of offers received. Most clients are toxic and expect to rank 1st on Google with a subpar service they charge a premium for. Take good care of the top 5%, and they’ll do the same for you.
So, you’ve decided to give this whole data-science-blog thing a try. That’s excellent news! Here’s a couple of things you should keep in mind:
- You must build a reputation first— Don’t expect any offers after a month of blogging. Take a year at least. Data science is so broad there’s no way you’ll run out of topic ideas.
- You can get hired as a data scientist based on your blog— But in reality, you’ll receive much more technical writing offers, at least according to my experience.
- You should charge a premium for your services— Providing data science services as a side job means you’re working with a client directly. There’s no middlemen involved like in your 9–5 job, which usually takes 80–90% of what you’re worth. Learn to take advantage of it.
- You can take it full-time— There will come a point at which you’ll have to choose — stay at a full-time job and enjoy the benefits, or become your own boss and make more money than you could imagine, while working fewer hours. It’s up to you.
- You have to consider the challenges of taking it full-time— Transitioning from a data scientist to a data science content creator is more challenging than it seems. Most of us tech professionals aren’t too skilled with words, especially if we’re not native English speakers.
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