Chapter 85 Resumes

When applying to jobs, you’ll almost certainly be asked to submit a resume. Anyone can write a resume, but it’s critical that you submit a good resume when applying to jobs. We’ll discuss how to generate a good data science resume in this lesson.

85.0.1 What is a Resume?

First and foremost a resume is a short document that describes one’s qualifications for a job. More specifically, this document will include your contact information, a brief summary of your qualifications, your experience, and education. And, importantly, this document will be short (usually, no more than one page) and easy to read. This means that the document must be organized, well-formatted, and clearly written.

85.0.2 General Features

Before we jump into each of the sections on a resume, let’s review a few general features of resumes.

First, resumes are brief. Resumes should almost certainly not exceed one page. If you feel like you have too much to say in a single page, consider the organization and formatting of your current resume. Do not consider going to a second page. Those reviewing your application should be able to glance at your resume quickly and garner the information they need. Do not count on them turning to a second page. Instead, put all the pertinent information on that first page.

Second, bullet points are ok. Resumes are intended to be read quickly, so full sentences are not necessarily required. Bullet points are easier to read quickly than paragraphs. Thus, use bullet points on resumes.

Third, use action words. Action words that describe what you did for specific projects or at a previous job should be used on your resume. And, the words you use should vary. If you led a project, you could use “Chaired,” “organized,” or “oversaw.” If you carried out the work on a project you may use “developed,” “designed,” “implemented,” or “devised.” If you saved your company money with the results of a previous analysis, you’d use words like “conserved,” “reduced,” or “decreased.” The purpose of these examples here is not to state the best action words to use on your resume, but rather it’s to demonstrate that there are a lot of action words out there. Use them. And vary the ones you use. Don’t simply use “Developed” over and over again throughout your resume.

Fourth, your resume should be organized and well-formatted. The goal of your resume is for a hiring manager to look at your resume, learn about you, and want to hire you at a glance. Thus, be sure that the hiring manager is not focused on the poor spacing, the small font, the hard-to-read color, or the disorganization of your resume. Be sure that the most important information jumps off the page and that nothing is hard to read on your resume.

Fifth, when organizing your resume, put information in reverse chronological order. This means the most recent things should be first within a section and the oldest things should be last.

Finally, everything on your resume must be truthful. Do not falsify any information on your resume. Do not include things you plan to do but have not yet done. Lying on your resume is never acceptable, no matter the circumstance.

85.0.3 Formatting

To ensure that your resume is formatted appropriately, we’ll discuss a few guidelines here. At the end of this lesson, we’ll include a few sample resumes though and you’ll see just how vastly resumes can differ visually and still be good resumes.

85.0.3.1 Fonts

The font you use on your resume should be easy too read. Avoid script fonts or ones that look like something a small child would write. Stick to fonts that can be read with ease. Times New Roman has been used historically; however, Helvetica, Arial, Verdana, and Calibri are also easy to read.

85.0.3.2 Font Size

Your name will likely be the largest piece of information on your resume. However, nothing on the page should be hard to read. Generally, for most fonts, the smallest font size you should use is 10 point. Section headers should be larger than the smallest font on the page but smaller than your name.

85.0.3.3 Colors

Sometimes, resumes will use color. This could be used to make your name and section headers stand out. Stick to colors that will show up regardless of whether the document is printed in color or black and white. This means that darker colors are safer. Navy blue or deep purple are better than sky blue or pastel purple, for example.

85.0.3.4 Be Consistent

Don’t use too many different colors. If you use a color for one section header, that exact same color should be used for all the section headers. The same goes for font and font size. Do not distract readers by using lots of different fonts. And, be sure that each element of your resume uses a consistent font size. Text in one section should be the same size as text in another section. Section headers should all be the same size. Spacing between the sections should be consistent. Consistency is key.

formatting matters

85.0.4 What to Include

Now that we’ve covered some resume basics, we’ll step through what you should include on your resume.

85.0.4.1 Name & Contact Information

First and foremost, your name and contact information should be included and should be at the top of your resume. This will include your mailing address, but should also include an email address and phone number. Further, for data science jobs, you should also consider your GitHub username and personal website. This will be a recurring theme in the lessons throughout this course. From each location, be it your resume, GitHub, or personal website, viewers should be able to easily access all other platforms where your information is stored. It should be easy to navigate to information about you between all platforms. That said, it’s not necessary to put your LinkedIn or Twitter handle on your resume, unless the employer requests it.

85.0.4.2 Brief summary

While the general rule for resumes is that bullet points are ok, the summary is the one exception to that rule. This should be a short (2-3 sentences) paragraph that summarizes your qualifications for the job to which you’re applying and what you’re looking forward to doing at that position. While most of the information on your resume does not change as you apply to different jobs, this section should change and be specific to the job to which you’re applying.

85.0.4.3 Skills

In addition to stating who you are, how to get in contact with you, and where to learn more about you, it’s imperative that your resume highlight the pertinent skills you have for the job to which you’re applying. For data science positions, this section should specifically explain your programming and data analysis skills.

If you’ve completed the courses in this course set, you’d be sure to include that you are comfortable in R and are skilled at data wrangling, data visualization, and basic data analysis. However, for any skill you state you possess, you should demonstrate examples of actually having and applying these skills in your experience section (discussed below).

85.0.4.4 Education

Your educational history should be included on your resume. Each entry should include the institution, what degree or diploma you earned, the years in which you attended the institution, and the city and state where that institution is located.

This section should also include online programs (such as this one, once you’ve fully completed it!) and any pertinent other job training, such as workshops attended or other pertinent certificates earned. Note that you should not include certificates you’ve earned that are not related to the job to which you’re applying.

Once completed, this Course Set should be included in this section. However, you should not include this on your resume until you’ve completed the entire Course Set.

85.0.4.5 Experience

Finally, your previous job experience should be included here. If you have years of data science experience, then it’s not necessary to include other, unrelated jobs. However, if you have years of job experience demonstrating your commitment to working for a company for an extended period of time but don’t yet have data science experience, put this job down. Employers want to see that you have worked at a job for a period of time.

After stating the employer, your title, and the location of each position, it’s customary to include bullet points of your responsibilities and projects worked on while employed. This is where it’s crucial to use bullet points, action words, and to be clear and concise. This section demonstrates to the employer your experience and what role you played at your former positions!

If you don’t yet have pertinent job experience, this section should include information about projects you’ve worked on.

85.0.4.6 Projects

This section is not generally required, as the bullet points explaining what you’ve done at previous jobs should explain the projects you’ve worked on and the role you played. However, if you don’t have formal data science experience working with a company, it’s incredibly important to demonstrates what projects you’ve worked on. These could be projects you’ve worked on throughout your coursework in this course set.

Or, these could be projects you’ve worked on on your own. We’ll talk about your project gallery and what it should include in a later lesson; however, it’s important to show to employers that you’re interested in data science work and have worked on projects on your own time. These projects should certainly be included and described on your resume, especially if you do not yet have official data science experience.

85.0.5 Example Resumes

To demonstrate how to format a data science resume, we’ll walk through a few examples. Note, none of these examples are actual data science resumes for real people. Rather, we’re using these as templates to highlight how to organize a data science resume.

85.0.5.1 Classic

Historically, resumes have not been visually stunning. They’ve been clear and well-organized with a focus on formatting; however, they have been visually standard with one section after another. Bold and underlined text have been used to highlight text with section headers sometimes being a different color and generally being a larger font size.

Here, we see an example of one such resume:

classic resume

We’ll highlight a number of features of this type of resume to draw your attention to important aspects of a data science resume.

First, notice that the applicants name and contact information are right at the top of the resume, and the name in particular stands out.

Name and Contact Information are prominent

Second, note that the font size, spacing between lines and sections, and chosen fonts are consistent throughout the resume.

consistency is key

Additionally, the expected sections are present and separated visually from one another. Further, within each section, bullet points are used and the text are aligned consistently from one point within the section to the next

expected sections are present visually separated

Note that no resume is perfect. In fact, there are many things that could be improved about this resume. For example, white space is to be avoided whenever possible on a resume. So blocks of white, empty spaces are opportunities to explain what you’ve done. This does not mean that you need to add more text to fill space. Rather, maybe font size could be increased or a different layout would have been able to display the important information more effectively.

Additionally, the Projects section could use work. There are too many bullet points for Projects. Three to four bullet points for any one topic is usually plenty. We would want to see if we could remove one of these bullet points. Also, the bullet points are smushed up against the underlined project name. It would be best to add a small space after the project name and the bullet points.

Blank white spaces should be avoided & spacing and bullet points could be improved

After noticing these, we would want to go back to the resume and make these improvements before applying! Your resume will be one of the first things seen by your possible future employer. You want to be sure to put your best foot forward!

85.0.5.2 Creative

Recently, with the frequency of data scientist positions within smaller startups, there has been some room for flexibility and creativity in data science resume design. Going with the classic design is a safer route; however, for positions where creativity is something the position is looking for, it may be ok to go with a somewhat different resume design. Here we see an example of a less traditional resume. Information very similar to what was seen in the last example is displayed; however, the formatting is very different. We’ll similarly walk through this resume design highlighting what it does well and where it could be improved.

creative resume

As we saw in the last example, the applicant’s name and contact information are clearly at the top of the resume. Here, the addition of small icons makes this information slightly more appealing.

name and contact information are visible and visually-appealing

However, unlike in the classic view, sections are not spaced one on top of the other. While all the same sections are still there, the page is separated using one gray block in the middle to highlight projects the applicant has used. And, sections are separated using either blue text, or white text within blue shapes. These do not all start at the left end of the page. Instead, they can be either on the left or in a second column on the page.

Spacing, coloring, and layout differ in this resume

As mentioned above, no resume is perfect. Maybe the gray is a little too dark. Maybe you wish you had more room to talk about your skills, as you did in the traditional resume view, but that you don’t have with this layout. Or, maybe the hiring manager won’t like this type of resume, as it’s not what they’re used to looking at. By choosing to use a less-traditional resume type, you’re taking a risk. It may make your resume stand out, or it could confuse be something the company doesn’t like. Know that there are risks behind using a less-traditional resume. It’s important to consider the limitations of your resume and the changes you should make to improve it before submitting it with your application!

Creative resumes layout limitations

85.0.7 Summary

In this lesson we’ve reviewed the general guidelines for resume writing, the important features of any resume, and a few examples of data science resumes. It’s best at this point to get working on your resume. You’ll be asked to submit a link to your resume in a lesson later in this course as a quiz response. And, while you’ll always have to update this document and there will always be ways to improve its appearance, the hardest part is getting a first draft, so get working on that now!

85.0.8 Additional Resources

Data Science Resume Examples
Advice for Applying to Data Science Jobs
Example Resume Templates - Classic ; Creative