7 things really worth focusing on to land a Data Analyst job
Forget those certifications. Here are 7 things that are really worth putting your energy and focus on if you want to land a Data Analyst job.
During my job search, I read a lot of articles online and watched a million Youtube videos on how to land a Data Analyst job. Turns out some tips were helpful but there were a lot of things that really helped me wow potential employers that were not mentioned anywhere.
So, after landing a remote position at a global Customer Experience company and rejecting an offer from TikTok, here’s my take on what you should really be doing to become a Data Analyst.
1) Sign up to newsletters about data and the industry you want to work in
When you’re on your own searching for a job, it’s easy to feel like you’re not really part of the data analysis industry until you get a job. But actually, you don’t need an invitation to join the conversation.
In the very early stages of my job search, I signed up to newsletters about data and music, which was the industry I wanted to analyse data in. This really helped me decide what types of jobs I wanted to apply for and gave me lots of pointers to bring up in interviews. I felt like interviewers were very impressed when I would bring up recent news or interesting concepts I had read about previously.
Some examples of newsletters I signed up to included data.world, MIDiA Research, Chartmetric, and Luminate. I also ensured I received daily e-mails from Medium with curation of articles on data and music.
2) Stop taking courses
You probably don’t want to hear this halfway through your Coursera certification but I’m not going to sugarcoat it for you: taking courses will have absolutely no impact in your ability to get a job. Anyone can sit in front of the computer watching videos for hours and do some fairly superficial exercises. They may help you get acquainted with the world of Data Analysis, but it just doesn’t make you stand out.
At the beginning of my journey to become a Data Analyst, I did take the Coursera certification and a SQL course on Datacamp because I didn’t know where to start. However, I never listed these in my CV and was able to land a job anyway. I wish I had spent all that time on activities that did end up helping me stand out from other candidates.
3) Instead, use that time to build your portfolio
What if there was something that could improve your data analysis skills, demonstrate to potential employers that you’re genuinely passionate about data and set you apart from other candidates?
One thing that is going to tick all those boxes is your portfolio. There was a crucial moment in my job search in which I realised that, in order to become a Data Analyst, I didn’t need to wait for a job offer or a course certification. I just needed to actually analyse data!
I’m going to write a more detailed article on how to start doing your first analysis but here are some examples of where to start:
- Download a dataset from Information is Beautiful and analyse it.
- You could then publish your findings here on Medium and/or upload your findings to Github. Make sure you have links for these in your Linkedin page.
- The Youtube channel Alex the Analyst has some guided analysis too that could inspire you.
- If you’re a good communicator, why not start a Youtube channel or a podcast to talk about your findings and put yourself out there?
4) Attend data conferences
Similarly to the newsletters in tip 1, attending data conferences will not only give you a repertoire of talking points for interviews but it will also allow you to get to know companies in your industry and connect with people.
Besides, as I mentioned, you’re a Data Analyst even before you get a Data Analysis job. So why not approaching some companies offering your services? In one of the conferences I attended, I ended up approaching a company afterwards and landed my first freelance project. Being paid for my Data Analysis work gave me a boost of motivation and the project looked really good on my portfolio too.
Which data conferences you should attend will depend on the industry you’re interested in, but I took part in the Measure of Music plus some Audiense and data.world webinars.
5) Start applying for jobs asap
Another thing I regret not doing earlier was applying for jobs. I thought I needed to wait until I had certifications, the perfect skillset, and a glowing portfolio before sending any applications.
Don’t wait. As soon as you have at least one thing to show for in your portfolio — and it doesn’t need to be a super complex project with visualisation and storytelling, a guided analysis will suffice — start setting up job alerts and apply for anything you think you may be just about suitable for.
You probably won’t land the job at the first interview (or maybe you will, but I certainly didn’t). But by applying for jobs early on you 1) get acquainted to the job market and what skills are in demand and 2) get in that mindset of interviews and selling your skills to employers.
6) No data experience, no problem
If you have no Data Analysis experience, you probably read the tip above and thought your CV would just look completely bare initially because you have no proven technical skills. If you’re in this situation, I would like to introduce you to your new best friend: transferrable skills.
Aspiring Data Analysts often think that employers are only looking for Excel gurus and SQL heads. What if I told you that the job offer I ended up taking required no SQL skills at all? In fact, I work mostly with Power BI, a tool I have never even touched. However, employers know that technical skills can be picked up on the job but it would be harder to teach analytical skills, numeracy and storytelling.
So, think about your previous experiences in work or education: have you ever had to analyse anything? Or maybe you had to make a decision based on data? Or just crunch some numbers? Even if these things are not enough for some positions, don’t underestimate them. And this goes to experienced Data Analysts as well: a good CV isn’t just about technical skills, so don’t forget to include important soft skills too.
7) Don’t let a No discourage you
Easier said than done, I know. It’s difficult to receive a No when you’re starting out in a new career and you’re already not sure if you’re capable enough. A single rejection can make you doubt all your hard-earned skills.
What I would say is: trust the process. Things will not happen magically and, as long as you keep putting in the effort, opportunities will eventually come up. Remember why you’re doing this: you’re passionate about data. A job offer will be just a natural consequence of your passion and hard work.
I received a lot of Nos during my job search but I would keep calling myself a Data Analyst. I continued to do freelance work, building up my portfolio, staying up to the date with the industry, and studying analysis techniques. And, even though I now have a Data Analysis job, I’m still doing all these things on the side. After all, I feel like a good Data Analyst never stops learning.
