4 Improvements For Your Data Science Resume
By: Matt Przybyla
Tags: Data Science, Towards Data Science, Artificial Intelligence, Resume, Machine Learning

Table of Contents

Introduction Highlight Projects Style of Writing Style and Format of Resume Mission Statement Summary References

Introduction

A resume is something that always seems like it can be improved upon, however, the most important thing for you to do is understand advice and apply it in your special way. What I mean by that is if you asked 100 professional data scientists and recruiters, they could all probably say something about your resume that needs to be approved. However, these improvements can also be subjective and you should take them with a grain of salt. The goal for you should be to learn as much about resumes, research data science-specific resumes, and apply that advice so you are improving your resume while also staying true to yourself.

For example, I have successfully been offered jobs even with applying with a blue resume. Yes, some companies do not prefer this style, but I do, and I wanna work for a company that does not see that style as a negative and instead, thinks it is something unique. The way I see it, you, the resume, and the recruiter along with the company serve as a matchmaker, all parties involved want what is best for them, so it is important to not show something just because you think that is what they want to see, but instead, show off your resume that highlights who you are. With that being said, let us dive deeper into these three ways that you can improve your data science resume.

Highlight Projects

Photo by Jo Szczepanska on Unsplash [2].

While reputable companies listed can be advantageous, it is important to keep in mind the main point of a resume — that is, showing off your experience. As you stare at your resume for hours, and are familiar with your work, it becomes easy to forget that the recruiters and hiring managers do not know your history. That is why everything you include on your resume can be significant in determining if you land a job.

Here is an example of how you should not and should highlight a project:

Bad example:

Uber (2020 — current)

Worked with team to use Data Science to solve the top 3 issues in the business development branch of the company.

Good example:

Uber (2020 — current)

Created an automatic classifier using Random Forest to save the company 50% time and money.

In the first example (bad), you can see that experience was highlighted, but a project was not. In the good example, you can see that a specific project was highlighted instead, as well as a few other qualities that I will be discussing below.

Style of Writing

Photo by Glenn Carstens-Peters on Unsplash [3].

As previously mentioned, highlighting projects is incredibly important to your resume, and even more important, is how you highlight them. For instance, in the above example, we saw a good version of highlighting a project. This example also was displaying the style of writing that you should include on your resume.

The main style is the following:

what, how, and effect

what you did

how you did it

and what is its effect

What you need to do is follow this format, while also incorporating the specifics of your project.

Here is an example of what you could do:

Automatically classified products (1) by developing an XGBoost algorithm (2) that reduced manual grouping by 60% (3), ultimately saving 2X of our operating costs (3).

1 is the what, 2 is the how, and 3 is the effect — which, can, of course, be two parted. This is an easy format to remember, and you can use this format for all of your projects. It is simple and easy to understand the impact of what you did and what tools you used to get there.

Style and Format of Resume

Photo by Alexander Andrews on Unsplash [4].

Perhaps the most subjective improvement you can make on your resume is the actual style of it completely. While there are certain styles of writing you can adhere to, this improvement makes less of an impact on some recruiters and hiring managers, while to some, it may draw them into your resume more. Like I said earlier, the style of your resume can serve as a way for you to know if the company values something special to you. For example, some companies prefer a bland, black and white resume, while some prefer something that stands out, which can be in a variety of forms. On the other hand, some companies may not care at all.

However, there is one style that I think is universally accepted by companies. That style is essential to make your resume not busy-visually. What I mean by this style is formatting your resume, no matter the color, theme, or order of how you structured your resume, to create negative space so that the reader of your resume is drawn to the points and information that you want to highlight.

Here is a poor example:

Showcasing the company, dates, projects, skills, and education, all next to one another so that the reader is confused on what to look at first.

Uber (2020 — current) - Worked with team to use Data Science to solve the top 3 issues in the business development branch of the company. Skills Java, Python, HTML, Pandas, NumPy Education University of Texas at Austin (2018 - current)

As you can see, this example is difficult to look at. I am not sure what to focus on first, even with an overall good order of company, skills, education, the format, the placement of these parts is visually unappealing — do not do this.

Here is a good example:

Uber (2020 — current) Created an automatic classifier using Random Forest to save the company 50% time and money. Skills Java, Python, HTML, Pandas, NumPy Education University of Texas at Austin (2018 - current)

As you can see above, this format is essentially the same information as the bad example, but it is highlighting the company, skills, and education with a bold format, while also having a clear, visual order of parts, and each part describes the section well.

Showing the company, dates, projects, skills, and education in visual order, so that the reader can go from the top of the resume to the bottom of the resume, without something else being in the way is the way to go.

Mission Statement

Photo by Markus Winkler on Unsplash [5].

This last improvement to your resume might be the most unique. I had originally not included this part in my resume, but eventually did, and got a great response from recruiters and hiring managers. What this improvement is, is a few sentences highlighting your mission in data science. It is a way to freely display your goals and specializations.

For example, here is my mission statement section, which is defined as “goal”:

Seeking a role to make a difference as a Data Scientist, where I can abide in my passion for the community by creating, evolving, maintaining, and ultimately revealing meaningful insights that support and validate relevant, data-driven change. To satisfy my curiosity and challenge myself by using my multidisciplinary background to implement scalable, statistical analysis, and beautiful visual assessments.

Mine may be on the longer side, but for me, that was worth the risk — because it highlights so much of who I am and what I want. This section can be much smaller, while also highlighting what about you is important and relevant to the job that you are applying for.

Summary

I have discussed some of the improvements that I believe will help you land a job, ultimately by making your resume better. Of course, it is important to take any advice with a grain of salt, just make sure what you change in your resume is because you want to, and is true to yourself and your work. Overall, we have discussed a variety of improvements like highlighting projects, the style of how you highlight those projects, the style of your resume format, and the inclusion of a mission statement.

Here are all of the improvements once more, summarized:

* Highlight Projects * Style of Writing * Style and Format of Resume * Mission Statement

Also important to note is that all of these resume improvements can be applied to non-data science roles as well.

I hope you found my article both interesting and useful! Please feel free to comment down below if you have leveraged any of these data science improvements for your resume — and which ones? Has it helped you in your Data Science career now? Do you agree or disagree, and why?

Please feel free to check out my profile and other articles, as well as reach out to me on LinkedIn. I have no affiliations with these mentioned companies.

Thank you for reading!

References

[1] Photo by Clem Onojeghuo on Unsplash, (2017)

[2] Photo by Jo Szczepanska on Unsplash, (2018)

[3] Photo by Glenn Carstens-Peters on Unsplash, (2017)

[4] Photo by Alexander Andrews on Unsplash, (2017)

[5] Photo by Markus Winkler on Unsplash, (2020)