Tips To Land A Data Science Role in 2021

When it comes to landing a Data Science role there is tons of Advice regarding the generic interview process, the type of non-technical questions you could be asked, as well as the technical ones so it makes sense to leave that department.

When I was going about my landing my internship, which would have been my first role related to data, I knew that my CV wasn’t appealing since I had no prior experience and I didn’t have a compelling academic background to lean on.

As a result, I was forced to come up with creative ways to get my foot in the door in a fashion that could potentially bypass the generic interview process where I’d be competing with much better prospects or at least get my name in the mix so that I could go up against them as a candidate. Either way, it didn’t matter. My theory was that if I could have more opportunities then the chance of me landing a role was higher.

With that being said, here are some of the things I tried before and some Ideas I’ve had over time.

Network

It is imperative I started with this because this is how I ended up landing a job. Much of the interview process is about the employer trying to distinguish whether you’d be a good fit for the company (and whether you feel the company suits you), hence this stage could almost be completely taken out of the picture [in some instances] if you’re able to forge a genuine relationship with recruiters or HR before you decide to apply for a role.

If you think about it, once a Data Science role has been shared for others to apply for the recruiter could potentially get 300+ applications per week! The chances of my CV being pulled out are quite slim, and if it is pulled out, I’ve got less than 60 seconds to impress that person who already has 300+ more applications to look at as well as other responsibilities.

Instead, it would be much better to find some recruiters or hiring managers on LinkedIn (apparently Twitter is good for this too) and begun engaging on their posts before ever reaching out to them – Yes! you don’t have to start a conversation straight away.

This way you aren’t a stranger when they post a role and you decide to reach out to them in the DMs, hence making it much more likely for them to reply to you when you send them a message to consider your application for the role.

Build A Portfolio

I’ll tell you a little story. I had just completed the Machine Learning course by Andrew Ng on Coursera and I really wanted a job so I did a project and added it to my Github account. I was tipped off about an app called "Meetup" and was told to look for Machine Learning events on there so I did and ended up at a practical IBM meetup where we used deep learning techniques to do artwork – pretty cool stuff.

I could feel myself needing to use the restroom – for a number 1 for your wondering mind – and by the time I got back someone had taken the seat I took up at the back so I had to sit right at the front next to some guy with a massive beard.

For the task, we had to fork some work from Github so I went to my Github portfolio, and the mysterious bearded guy jeered "Hey man, how come your one is full?", "Oh, I already had an account. The files there are from some Machine Learning projects I’ve done" I replied. From then I didn’t really pay much attention to him but occasionally he’d ask for a hand on some task and I’d help out.

At the end of the event, he asked if I could quickly run him through the projects so I did so. He loved it so much that we exchanged contact details. 2 months later, he gave me a call back to come present what I’ve done to some of his directors. I ended up landing a job there and the bearded mysterious guy became my line manager.

Now. I’m not saying this is how it will go down for you if you complete a project but having something tangible there to display what you bring to the company goes a long way in landing a Data Science blog.

Start A Blog

After a few months of my internship the same bearded guy, now my line manager, suggested I start a blog to help me improve my communication skills when dealing with a non-technical audience. I heeded this advice and my goodness I’m so glad I did.

My network has vastly expanded as a result of my blog and I am constantly bombarded with opportunities to do some cool data-related work. In fact, my break into freelance work was a result of my blog which has been my financial support whilst I upskill.

Note: However, a major tip I’d say to anyone starting their own Data Science blog is that you should try to ensure your goals isn’t about becoming super famous or making lots of money. Instead, let it be because you genuinely care about others so you share what you’ve learned.

If this is at your core then you’d be much more prudent about the work you put out as you wouldn’t want to mislead people and if you’re diligent with your quality and consistent with your posting, overtime the fame and finances will come as a by-product.

Practice Interviews and Assignments

I know I said we’d ideally want to skip this but it would be ignorant of us to not practice this step in the first place. Regardless of whether you have a job interview scheduled or not, if you know you’re job hunting then you should be practicing your interview skills [technical and non-technical] and doing some practice take-home assignments to keep your skills sharp.

As I mentioned at the start of this post, there are tons of resources already online for this. To name a few:

These are just a few but you can most definitely do a deeper search to find questions more related to the roles you’re interested in.

Wrap Up

Other than these tips there are the general mindsets that ought to be adopted when job hunting such as persistence and learning from your failures. I don’t have many tips for CV’s but I would say it’s always better to have a relationship built with someone that you wish to provide your CV because they are more likely to take time to look at it and consider you as a candidate than a cold application.

Tell me what you think of these tips.

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