3 Mistakes Prevent Your Data Science Resume From Standing Out (Copy)

Time to Recruit! 

The approval of a new open position on the team is always an opportunity to expand and include new perspectives and voices on the team. But it can also mean anxiety due to the influx of resumes. For the latest job opening I had over 400 applications in my inbox. This seems like a good problem to have, right? It is until you consider that only a fraction of them were worthy of consideration as a good fit for this particular position. 

Don’t get me wrong - I understand the strategy of job seekers casting a wide net and applying for many positions, hoping that something sticks. If this is your approach to applying, I appreciate it. But what if this position sounds like a perfect fit for you and you are very passionate about it and really want to stand out as the best candidate for the job? 

Then avoiding these three mistakes will help your resume stand out...

Mistake #1: Using incorrect spelling/poor grammar

This is less of a “standout” technique and more of a “get in the door” technique - misspelling words and using poor grammar indicates that you either did not put in the effort or did not pay attention to the details. In either case, you are probably not a good fit. Basic effort and attention to detail are key to landing and succeeding in a good data science job. Lack of these two things will quickly land you in the “reject” pile, without even getting to the end of your resume. There are a myriad of spellcheck and grammar tools out there. Use one and get in the door!

Mistake #2: Not connecting your experience to the job requirements

Going back to casting a wide net, many candidates submit their resume without giving too much thought to the requirements stated in the job description. For example, despite the job description requiring at least 2 years of industry experience, candidates who are finishing graduate school and have no industry experience apply.

Again - I empathize with the strategy of casting a wide net and applying for jobs whose requirements you don’t meet fully, and you might be that diamond in the rough that might justify hiring them anyway. But you have to EMPHASIZE THAT intentionally!

Consider that there is a reason why industry experience is required. It shows you have dealt with and solved real-world problems with real-world data, and not just worked on academic projects that were very isolated and geared towards a specific measure or outcome. And yes your class project using Spotify data to recommend new songs uses real-world data, but you didn’t have to coordinate with stakeholders and change requirements midway through and communicate to non-technical teams and other real-world situations that industry experience undoubtedly puts in front of you.

What can set you apart is detailing how your experience relates to the requirements stated in the job description. Beyond using buzzwords, show how your specific experience can be valuable to the tasks the company will expect you to do. If you lack certain experience, what can make up for it? Why should they hire you regardless? And this leads to the last tip…

Mistake #3: Including a generic cover letter

Cover letters are optional but if you DO decide to include one, make sure it moves the needle in your direction and that it adds value! Generic cover letters stating that you are a self-starting go-getter that’s passionate about data and analytics won’t cut it. 99% of cover letters say that.

So ask yourself - What sets you apart? Personalize and tailor the letter to the company and its goals and challenges. What about you is SPECIFICALLY geared towards helping the company achieve WHICH goals? This requires some research about the company, what its goals and challenges are, and which of your skills can help with achieving those goals and overcoming those challenges. Hiring managers, when reading resumes and cover letters, look at them through a lens of “what’s in it for me?”, and spelling it out explicitly will set you apart.

The Take-away! 

While these tips are no guarantee of getting a call-back, the more a candidate is thoughtful about the position and the more they address the requirements and unique goals of the company they are applying for, the better the chance they have of standing out and moving from the “reject” pile to the “maybe” pile or even to that coveted “callback” pile.

Make sure to avoid these mistakes and you'll be wearing the Chanel boots in no time!