4 Must-Haves for the Data Job Hunt

Hey everyone 👋

Big announcement before we jump in…

I started my YouTube channel this week 🥳

I’ve been wanting to do this for a while now. I just have one video so far, but it would mean the world to me if you could visit the channel and subscribe.

Here’s the channel 👉 https://www.youtube.com/@MattMike

More to come!

Alright, let’s jump into our topic for this week….

A well-rounded approach to the data job hunt.

Sometimes when I post about tech skills I hear this response, “I have those skills but I still can’t get a job.”

This is a very narrow view of what it takes to get a job in data.

And honestly, when I hear it I’m not too surprised to hear they’re still looking.

That’s because it takes MUCH more than having the right tech skills to successfully land a data job.

Here are a few other things to consider outside of learning tech skills.

1 | A Solid Portfolio

And when I say solid, I mean solid. What does a solid portfolio look like?

• 3-5 projects

• A smooth landing page and repository of said projects

• Each skill in your tech stack represented in at least one project

In addition, I often recommend posting about your projects. This draws opportunities to you, but more importantly, you’ll get FREE feedback from the data community. It can be scary to post, but it’s worth it.

One last note here, just because you have projects doesn’t mean they’re good. I recommend creating lots of projects to hone your skills and to seek as much feedback as you can.

2 | A Well-Written Resume

This one is obvious, but it may surprise you how many resumes I see that are not….well, good.

Just like I mentioned with the portfolio, simply having a resume isn’t good enough. You have to make sure you’re resume is a knockout. This is another area where you’ll want to do your research and seek feedback, ideally from a professional and/or someone already in the field.

3 | Strong Interview Skills

Making it to the interview is one thing, but acing it is another.

I recommend writing down a list of situational examples from work that you can speak to in your interview. Have about 5-10. Use STAR to practice your responses to these questions. S = situation; T = task; A = action; R = result.

Be prepared for any technical interviews.

You should also be ready to talk through some of your projects. Don’t wait for them to bring it up. Try to bring them into the conversation on your own.

Lastly, be personable. No one wants to hire a robot. Just be yourself and do your best to be relaxed.

4 | Building and Leveraging Your Network

Getting involved in the LinkedIn community is one of the best things you can do for your career. It’s an incredible platform for getting to know others in your field and creating opportunities.

This is where posting and engaging on other people’s posts is so important. This breaks the ice in getting to know others and sets a foundation for a conversation over DMs.

Reach out to people who work for your target companies and try to strike up a connection. The worst that could happen is they ignore you. The best that could happen is you get a job.

Just put yourself out there online. You might be surprised at the connections and opportunities that come your way.

PS - I’m getting ready to launch a more formal, 1:1 ongoing coaching program for aspiring data analysts. I’m incredibly excited about this. It’s going to provide a TON of value.

That’s it for this week.

See you next time

Matt ✌️ 

Whenever you’re ready, there are 2 ways I can help you:

1 | The Data Portfolio Guidebook

If you’re looking to create a data portfolio but aren’t sure where to start, I’d recommend this ebook: Learn how to think like an analyst, develop a portfolio and LinkedIn profile, and tackle the job hunt.

Join 500+ learners here

2 | 1:1 Coaching

For help navigating the data job hunt, consider booking a 1:1 career guidance session with me. There are a few options available to help you get to your ideal data job faster.

Schedule a 1:1 here