5 Common Mistakes to Avoid to Successfully Navigate the Data Job Market in 2024

Lessons from coaching 50 aspiring Data Scientists

Back in 2017, when I first stepped foot into the job market in search of my first data job, the landscape was completely different.

It wouldn’t be an exaggeration to say that the job market was thriving.

Yes, competition was fierce, and landing that first data role wasn’t easy, but it was nothing compared to what it looks like today.

It is no wonder this post resonated with so many people…

This LinkedIn post reached over 360K people in less than a week.

This is of course a bit of an exaggeration, but is it really??

The “required” tech stack alone — or employer’s wishlist — for an entry-level position has gotten insane and unfortunately, the current job market doesn’t allow you to be too selective.

When I started, I would’ve benefited greatly from some mentorship, and seeing how difficult things are at the moment, I know those entering the job market probably need guidance more than I ever did.

This is why, over the past four months, I have coached over 50 aspiring data scientists (mostly for free) to give them the strategic direction they need to step into the job market.

Today, I want to share 5 of the most common mistakes I’ve seen and that you need to avoid if you want to increase your chances of getting noticed by hiring managers and getting the interview you want.

1. Thinking data visualization only means Matplotlib

Being proficient at data visualization goes beyond just creating pretty charts.

As a Data Scientist, you will need to contribute to making data accessible to a broad range of users, basically be a champion for data democratization.

BI tools are often used to facilitate this process, making it possible for even non-technical stakeholders to make data-driven decisions without needing your help directly.

This is why, your data visualization skills need to go beyond just knowing how to use Matplotlib and Seaborn, you need to demonstrate your ability to work with BI tools.

That’s the type of relevant data visualization experience most hiring managers are looking for.

💡 My recommendation is that you start with Tableau since it’s one of the most popular BI tools out there and they offer a free public version. For more insights on which skills and tools are in demand, check out this Data Job Market Report.

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2. Treating every potential employer the same

Stop bulk applying and start using your time more strategically.

I’ve seen this time and time again, you think to yourself “The more I apply, the higher my chances”, so you start using the same resume and cover letter to apply for every job you come across and then wonder why you are not hearing back.

Your main objective when applying for a job is to show the recruiter and hiring manager that you are a strong fit for the role.

In order to do this effectively, you need to ensure your resume and cover letter actually fit the role you are applying for. 💡 These are some of the things you should be doing:

1. Using relevant keywords extracted directly from the job ad.

2. Only including relevant experience (this includes work experience and projects)

3. Showing potential employers why you are excited about their company (this is mostly for the cover letter)

The more jobs you apply to, the higher your chances of getting an interview, but only if your resume can effectively communicate how you are a strong fit for the role.

3. Adding every technical project to your portfolio

There is a difference between “projects for learning” and “projects for showing”.

You may have gotten a great education but without relevant work experience (e.g. Internship), you’ll have a harder time convincing hiring managers you are ready to join their company.

So, how do you bridge the experience gap? One effective way to do this is by building a strong data science portfolio.

But understand that there are projects whose only purpose is to help you learn new tools and techniques such as the “MNIST Handwritten Digit Classification”, and therefore should never be used as a portfolio project.

💡 You must avoid prioritizing quantity over quality and come up with project ideas that are unique and solve real business problems.

4. Messaging recruiters after applying for a job

This won’t increase your chances of landing an interview.

I used to fall for this trap too, believing that sending the recruiter a message along the lines of “I just applied for this role and this is why I’m a strong fit…“ would increase my chances of getting noticed in a sea of candidates, but the truth is, it won’t.

While it is important to make yourself stand out, this is far from the best strategy. Recruiters' inboxes are flooded with unsolicited messages from candidates asking for interviews, but these messages rarely get noticed because your application is expected to speak for itself.

A proven method to make yourself standout is getting a referral.

Referrals guarantee your application will be given higher priority and will not get lost in a sea of candidates. Research shows that candidates with referrals are three to four times more likely to get hired than those without.

💡 Lots of companies (mostly in tech) have a "referral incentive program" which makes it easier to find someone willing to refer you as long as you have the necessary qualifications and a good resume to demonstrate it.

5. Not letting go of irrelevant work experience

Crafting a strong resume requires making trade-offs.

This mainly tends to be an issue with career switchers who have a hard time looking at their resumes objectively and cutting out anything that doesn’t truly contribute to making them a stronger candidate. But I’ve also seen this mistake with those who simply want to fill up their resume with as much as they can to make themselves look more experienced.

Now let me be clear, crafting a resume is not easy, it has taken me years to get good at it, so make sure you do your research.

As a rule of thumb, If the work experience or skill doesn’t directly relate to the job you’re applying for, it likely doesn’t belong on your resume.

Remember, you have limited space, for entry-level roles, this usually means one page. Therefore, you need to include the most relevant information that will make the strongest impression on the hiring manager.

💡 Having previous work experience as a Project Manager is quite relevant for a Data Scientist role, but your experience as a Marketing Specialist isn’t unless the job explicitly requires it or you can clearly articulate how it involved using relevant analytical techniques or tools.

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Thank you for reading! I hope these tips will help you become more effective at navigating the current job market.

- Andres

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