Portfolios and LinkedIn profiles will only get you so far in your career as a Data Scientist.
Sure – LinkedIn is a great way to build a professional network, and portfolios provide a great way to showcase the cool stuff you’ve done. But if no one clicks on your portfolio link or you don’t want to become a LinkedIn hustler, your profiles will just sit there collecting digital dust and you’ll never get any value from it.
In this article, I want to advocate for another, complimentary strategy: writing online.
Until 3 months ago, I’d never written a single thing for fun, and most of my memories of writing were negative ones from school and exams. So if the idea of writing online sounds crazy (or out of your comfort/interest zone), I completely get where you’re coming from. But after 3 months of this practice, I’ve become a big believer in it and, if you give me 2 minutes, I’ll explain how writing online can enable Data Scientists to:
- Develop a strong personal brand
- Form meaningful connections with others in the Data Science community
- Develop the oft-neglected skills of storytelling and communication
- Showcase your skills in a recruiter-friendly, shareable format
Then, I’ll share some of the things which helped me get started with writing and give you some ideas for how you can get started, too.
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The 4 benefits of online writing
1. Writing helps you develop a strong professional brand
For most of my professional life working in data, I’ve taken a pretty standard approach to professional branding.
I created a personal portfolio, maintained a LinkedIn profile, and occasionally posted about a significant career achievement.
The problem with this approach is that portfolios and LinkedIn profiles are tucked away in an obscure corner of the internet. No one can find your stuff unless they actively go looking for it, and you haven’t really got a mechanism to get feedback on your work.
When you write online, by contrast, you’re able to share your work with a wider audience and get very good feedback on things like Reading Time and Read Ratios. If you persevere, writing is a fantastic way to build a personal brand and become the "go-to" person in a specific niche.
One of my aims, for instance, is to try and become the go-to person writing about Data Science Careers. It would be really hard to build that kind of niche brand if I were relying entirely on a personal portfolio or the occasional humble-brag-slash-inspirational LinkedIn post, but by writing on Medium, it’s easy to carve out that kind of online identity.
And don’t just take my word for it – look at someone like Cassie Kozykrov, for example. Cassie’s the Chief Decision Scientist at Google, and an incredibly inspiring person to follow in the world of Data. By writing online, she has carved out a fantastic personal brand which has meant that even clueless people like me know who she is. Or take Chris Albon, the Director of Machine Learning at the Wikimedia Foundation, who has probably the funniest Twitter account in the world of Data. Chris has built a fantastic personal brand through years of building up a great library, and he gets to use that platform to share great learning resources with people from all around the world.
2. Writing online helps you form meaningful connections with others in the industry
The next benefit of writing online is that it’s a great way to build your network and can be a much more enjoyable alternative to something like LinkedIn.
After years of posting on LinkedIn, I’ve noticed that there’s often a mismatch between the people who see your content and the people who you want to see your content.
Most of your viewers will be your followers, but unless you’ve already got a super active and engaged audience, you’re unlikely to have many interested followers. Your followers tend to be people who already know you, and – what’s worse – half of them are probably only uninterested semi-contacts. Heck, my LinkedIn network includes people I worked with in my first Saturday job at the local newsagents. It’s lovely to be in touch, but there’s not much value for either of us in me sharing my thoughts on the AI revolution.
When you write online, by contrast, you’re able to share your thoughts with very targeted communities in a way that’s much more sustainable and valuable in the long-term.
For example, I share most of my Data Science articles in publications like Towards Data Science and Towards AI. I’m able to target people who are in my field specifically, and I don’t bother randos with my musings on the nuances of Convolutional Neural Networks. When I share these musings on a platform like Medium, I’m able to get my content in front of people who are actually interested.
3. Writing helps you master communication and storytelling
Ask any Data Science recruiter and they’ll tell you that it’s easy to find someone who knows what an unsupervised ML model is. The hard thing is finding someone who can explain it succinctly to non-techie stakeholders elsewhere in the business.
As you develop your career in Data Science, it’s really important to build these communication skills, and you shouldn’t focus exclusively on technical skills. Sure – when you’re starting out, you might spend most of your time coding and not do much presenting outside of internal team meetings. But if you want to advance your career, it’s absolutely critical that you develop strong storytelling and communication skills. Remember: Senior and Principal Data Scientists spend a lot more time presenting than they do coding. Writing helps you do this because you’re constantly thinking about how to land your points well and where to cut down on the unnecessary fluff.
4. Portfolios are useful when you’re beginning your career; writing is more effective for advancing your career in the long-term
Something that lots of aspiring Data Scientists might not realise is that portfolios can quickly become obsolete.
I remember when I created the first version of my portfolio site, back when I was finishing my master’s degree in Data Science a little under a year ago. It was time to start applying for Data Science jobs, and I wanted a way to showcase some of the projects I’d been working on. I’d heard people talking about the importance of building an online portfolio, and so I whipped up a simple static site using GitHub pages and Jekyll.
While this portfolio was immensely helpful for getting my first jobs, as soon as I started working full-time as a Data Scientist, I found that I didn’t have time (or inclination) to do Data Science projects outside of work hours. Employers were also much more interested in my achievements at work than they were in my personal projects, and before long I’d given up on my portfolio.
Writing online, by contrast, has in my experience proven to be a much more sustainable way to build career capital in the long-term.
Why? Firstly, because it’s fast. Doing a full Data Science project takes a long time, but writing a quick blog post (like this one) can be done in an hour or two.
Secondly, because you can write about anything you want. This makes writing a very sustainable long-term strategy for building career capital, because you can change what you write about over time. When you’re "on the ground" working as a coder, you can share coding tips or project summaries. When you’re a bit higher up and spend most of your time meeting with stakeholders or figuring out team strategies, you can write about the big picture stuff. Regardless of which stage of your career you’re at, it’s super easy to share your online writing with technical and non-technical recruiters alike, and you get to demonstrate your communication skills "in real life" by showing how you write.
If you’re still not convinced, consider this: if the last year of AI developments has taught us anything, it’s that algorithms and coding languages may change, but storytelling skills will always be needed. In 5 years, I expect that AI tools will mean I’ll be doing a lot less coding (or, at least, my coding will be much faster). But I’ll sure as heck still be telling stories with data, so it feels like a good investment to work on this skill.
How to start writing
If the idea of writing online sounds daunting, don’t worry: I used to feel the exact same.
Then, in March 2023, I took the plunge and wrote my first article on Medium. Here are the dos and don’ts that helped me get started on this journey.
Do:
- Start small – You don’t need to write about something groundbreaking or super niche. My first article was a personal reflection on my career story, and my second was a guide on how to bin data with SQL. Both were only super simple topics, but this was actually an advantage because they didn’t take long to write about, making it very easy to "get the ball rolling."
- Share your personal experiences – There are tons of coding guides out there, and you’ll find it hard to stand out if your writing reads like technical docs pages. Regardless of what you’re writing about, try and show your readers a personal angle: if you’re sharing a coding tip or theoretical explainer, how has this {technique/concept} helped you in your personal job/project? How long did it take you to learn? Any advice on how to put your tips into practice?
- Find a rhythm that works for you – I post quite regularly on Medium because I enjoy writing, but it’s not the only way to do things. Plenty of great Data Science writers only publish once a month or once every few months. The key is to find a rhythm that works for you and stick to it.
- Write about evergreen topics – If you write coding guides or share personal stories, those pieces will remain useful for a long time after you’ve written them. Even if they don’t take off straight away, you’re investing in a long-term bank of quality content which will still be valuable if someone stumbles across it in 2 years’ time.
Don’t:
- Don’t feel like you need to be an expert – Even if you’re a beginner Data Scientist or an aspiring Data Scientist, I can guarantee that you’ve got something valuable to share. Readers don’t care whether you’ve got a PhD in Quantum Basket Weaving; they only care whether you can help them solve the specific problem they’re facing. My own profile is testament to the fact that you don’t need to be a pro or write about complicated topics.
- Don’t worry about finding a niche – Take your time to experiment with different topics, and leave the niche-finding to a later date. As YouTuber Ali Abdaal often advises, start by just "Getting Going," then focus on "Getting Good," and only later should you worry about "Getting Smart." Don’t constrain your imagination by imposing strict limits on yourself; allow yourself to try new things out and see what you enjoy. You might even surprise yourself!
And there you have it!
Thank you for reading. I hope you’ve found it helpful, and please feel free to reach out if you fancy a chat 🙂
Oh, one more thing –
I’ve started a free newsletter called AI in Five where I share 5 bullet points each week on the latest AI news, coding tips and career stories for Data Scientists/Analysts. There’s no hype, no "data is the new oil" rubbish and no tweets from Elon – just practical tips and insights to help you develop in your career. Subscribe here if that sounds up your street!