Introduction

A standout data science resume is a resume that will get you hired. Before it gets you hired it will get you an interview. Before it gets you an interview it will get you past the automated and human screenings.

In this short article I outline a handful approaches that will help you make your data science resume stand out ➡️ get you past automated applicant tracking systems ➡️ get you past human screeners ➡️ get you an interview and ultimately ➡️ get you hired.

Keywords, Keywords, Keywords

In the modern recruitment and selection landscape automated applicant tracking systems are a given. Automated applicant tracking systems (ATS) are software programs that scanning resumes for specific keywords and then rank them based on how many keywords they contain. This helps employers quickly and easily screen through large numbers of resumes, saving them time and helping to ensure that they only consider the most qualified candidates.

To do well in a job search your resume needs to be precisely fine tuned to match the job description key words. My favorite example of this would be where a job description lists "experience with Microsoft Office Software Products" but where the candidate might put "experience with Microsoft Office Suite." My listing Microsoft Office Suite instead of Microsoft Office Software Products the candidate will have missed a crucially important opportunity to match on that keyword.

Have + Showcase Your Data Science Projects

Having an impressive data science portfolio can be your secret sauce (if you set it up right). An interesting data science portfolio will make it easy for employers, recruiters, and prospective co-workers to remember you, think about you, and want to talk about you with others at all stages of the recruitment and selection process.

Essentially, a professional portfolio is a compilation of your best work. It can be in any form, but it is typically a collection of documents or artifacts that demonstrate your skills, abilities, and experience. Important to know, you do not need a website to host your portfolio. Also long gone are the days of carrying around a folder full of work examples. Instead, your portfolio consists of articles you wrote online (at Medium, LinkedIn, or on other similar sites), your GitHub repositories, and also sometimes simple posts on social media. A portfolio can also include examples of work from previous employers, such as reports, papers, articles, designs, websites, or software.

As you work to build your portfolio, and your online presence in general, be cognizant of opportunities to point resume readers towards your portfolio entries online.

Quantify your results whenever possible

After you make it past the automated applicant tracking screening systems you also need to make sure you do well with human screeners. One of the best ways to impress a human reader is to make information about your past work and accomplishments as tangible as possible.

There is a simple X-Y-Z formula that can help with this. Whenever you can, throughout your resume, explain exactly what you accomplished [X] as measured by [Y] metric by executing [Z] strategy, tactic, or initiative.

Always, Tailor Your Resume To The Specific Job

Please do not underestimate the importance of this step in the process. When you apply for a job, your resume should be tailored to the specific position you are applying for. This means that you should highlight the skills and experiences that are relevant to the job, and you should downplay irrelevant information. You should also be sure to use the keywords from the job listing in your resume. This will help you to pass the automated applicant tracking system and to impress human screeners.

Be specific. Above I gave an example related to keywords where a candidate may have missed an opportunity to keyword match because the candidate wrote "Microsoft Office Suite" instead of "Microsoft Office Software Products." Notice, that it does not matter if the job description used a title that Microsoft itself doesn't use to identify its products. What matters is that the job description match as much of the job description as possible.

Proofread + Edit Carefully

It's important to proofread your resume because typos and careless mistakes can cost you an interview. Hiring managers often receive dozens, if not hundreds, of resumes for a single position, so they are quick to weed out candidates who appear unprofessional or lack attention to detail.

A single typo can be all it takes to get your resume tossed in the trash. Two of the best automated writing assistants are Grammarly and also ProWritingAid.

Conclusion

There are many ways to make your data science resume stand out. This article describes five tactics that will help including:

• Matching keywords (very closely).
• Having + Showcasing Your Data Science Portfolio.
• Quantifying Results + Accomplishments.
• Tailoring Each Resume To Each Specific Job.
• Proofreading + Editing Carefully