Data Scientist Resume Example & Writing Guide

If you are a data scientist, you know that your job revolves around digging through heaps of data to uncover hidden clues, information, and insights. However, condensing plenty of valuable details about yourself into a data scientist resume is a whole new challenge.

When you’re used to working with huge datasets, it can be tricky to go in the opposite direction to try and fit a huge pile of material onto one page.

But fear not! Your profession gives you a solid foundation in data manipulation. With a bit of guidance, a few expert tips, and an example here and there, you’ll learn how to create a stellar data scientist resume that will pass any ATS scan and impress every recruiter.

So let’s get busy turning your document into an attention-grabbing masterpiece!

What is the Right Format to Use for a Data Scientist Resume?

You’re familiar with the importance of conveying complex information in a clear and concise manner. That’s why you need a strong format for your data scientist resume—to ensure you’ve provided all the crucial information recruiters want to read in an optimal way.

The chronological resume format is by far the most popular. It’s an intuitive, orderly format that emphasizes your latest job and achievements while listing the rest in reverse-chronological order. Its neatness is the main reason why it’s favored by recruiters and easily parsable by the ATS.

In addition to the chronological resume, there are two more formats you can use depending on the circumstances:

1. The functional resume format, which makes the skills section pop. It is recommended for entry-level candidates who lack work experience but have an impressive skill set. The downside of this format is that it might run into issues with the ATS due to its uncommon formatting.

2. The combination or hybrid resume format, which has the features of both chronological and functional formats. This format lists notable accomplishments under each skill, which makes it perfect for seasoned veterans or candidates with gaps in employment who have valuable transferable abilities.

Resume Layout

The purpose of a strong resume layout is to make your document readable and your sections visually distinct. 

First things first, it’s highly recommended that you fit all of your information onto one page. Many recruiters have to go through countless resumes, and they won’t spend a lot of time examining each one. You want to show them as much as possible, as quickly and clearly as possible, and the following tips can help you achieve that:

• Take advantage of bullet points, as they offer the same amount of information as paragraphs while being noticeably shorter.

• Pick a clean and professional font that’s easy to read (e.g., Calibri or Arial).

• Aim to have a text font size of 10–12 pt, with subheadings being 2–4 pt bigger.

• Use a combination of white space and 1-inch margins to define sections and organize them visually.

What Sections Should a Data Scientist Resume Contain?

Let’s talk about the actual contents of your data scientist resume.

By the end of this article, you’ll know precisely how to write each of these sections from scratch. Still, wouldn’t you like to speed up the whole process while ensuring a professional and error-free resume as a result? If yes, take a look at our resume builder.

You can start by examining ready-made resumes created by industry experts or downloading PDF samples of these data scientist resumes. When you find the template that suits you, adjust everything from its color to its fonts and sections, and then simply insert your details and download a finished resume!

Data Scientist Resume Contact Information

Let’s start our resume with one of the most clear-cut sections—your contact information. You should place the following details in your resume header:

• Your name and role

• Phone number

• Email address

Adding your location is an outdated practice due to security reasons and should only be used if you’re applying for a job abroad. What you can consider adding to your data scientist resume are LinkedIn and Github profiles, for example.

Here’s an example:

Make sure to keep this section spotless—especially your phone number and email address. On a related note, if you’re still using a “witty” email address you made to communicate with friends, it’s probably time to create a new, professional one.

Data Scientist Resume Objective or Summary

Imagine you only had a couple of seconds to introduce yourself to your potential employer. You’d want to start with your strongest skills and most impressive achievements. That’s the goal of a resume summary or objective, and you’ll put one or the other in your resume header next to your contact information, depending on the circumstances.

If you’re a data scientist with plenty of experience, you want to grab the recruiters’ attention with your most prominent professional accomplishments. In that case, you should write a summary and encapsulate your entire resume in 2–4 sentences.

However, if you’re an entry-level data scientist, a resume summary likely won’t do. Since you lack professional history, you should write an objective for your resume to highlight your key skills, motivation, and plans for the future.

Data Scientist Resume Objective

In addition to talking about your outstanding skills in your resume objective, you can include a few more details to spice it up, such as your degree or internship experience.

Here’s an example of how you can write a data scientist resume objective:

On the flip side, we have a bland resume objective where a candidate didn’t include anything of value to potential employers:

Data Scientist Resume Summary

When writing a data scientist resume summary, your goal is to condense your entire career into one or two remarkable achievements. Make sure to mention your experience and some skills that can separate you from less competent candidates.

Here’s a good example:

This resume summary is brimming with valuable skills and impressive accomplishments. Now compare it to the following poorly-written example that falls short in those aspects:

Data Scientist Resume Work Experience

As it’s usually the most important section, the previous work experience information is what recruiters will pay attention to first when looking at your data scientist resume.

Data Scientist With No Experience

Even if you don’t have a professional history in the field of data science, you can still make an irresistible work experience section. The only difference is that you’ll be using substitute endeavors, such as internships, freelance work, volunteer experience, and even college projects.

Here’s how a candidate leveraged their internship to create a remarkable work experience section:

Experienced Data Scientist

A senior data scientist resume should show what results all those years of experience have brought. As much as two-thirds of your resume can be dedicated to this section if you have multiple jobs to list in reverse-chronological order.

When including your achievements, focus on those that show how your employers benefited from your extraordinary abilities.

Let’s see that in an example:

Data Science Manager

When you’re applying for a position of a data science manager, demonstrating your leadership and management skills becomes just as important as showcasing your prowess in data science itself. Therefore, you shouldn’t forget to put the results front and center to show the impact that your competence had.

Here’s a good example:

Data Scientist Resume Education Section

The education section is another straightforward one with a simple format to follow. It goes like this:

• Your degree

• University name

• First and last year of attendance

• (Optional) High GPA, courses, extracurricular activities, projects, etc.

You should include the optional bits as bullet points if you have little to no professional history. Otherwise, it’s better to keep this section brief and let your work experience do its thing.

Another thing you can do is include a degree, even if you’re still a student at the time of applying for a job. In that case, you can either put an expected graduation date and mark it as such or place “current” instead.

Now let’s take a look at the example:

Data Scientist Resume Skills

How do you differentiate yourself in the sea of other data scientist candidates who have similar skills to yours? The answer is twofold—by:

1. Adding relevant skills to your data scientist resume

2. Proving them

Start by doing the research. You’ll find out what types of skills recruiters are looking for by carefully reading the job advertisement and researching the company. Once you do it, you can simply create a list of skills that will go right after your education section.

Keep in mind that the main focus of this part of your resume should be on your job-specific, hard skills. Only after including them should you include a shorter selection of soft skills. It’s also important not to mix these two lists together, as they are fundamentally different.

When it comes to proving your skill set, the best way to do it is through your work experience. Try to put relevant skills next to the work accomplishments you mentioned to show how your abilities helped you obtain specific results. This way, you’re not just making vague claims that you possess certain abilities—you’re giving actual proof.

Data Scientist Resume Optional Sections

Finally, you can give your resume an extra punch with some of the following optional sections:

Awards & Certifications

Awards and certifications can be vital in the field of data science because they demonstrate both high levels of expertise and commitment to the profession. Listing them on a resume is one of the easiest ways to stand out among the competition.

It’s also common practice to include your awards and certifications in reverse-chronological order, focusing on the latest first. However, make sure to only list those that are relevant to the position that you’re applying for.

Furthermore, you should mention some relevant details, such as the name of the certification or award, the organization that granted it, and the date when it was obtained. You can also briefly mention what the certification signifies—any particular skill or knowledge area covered—or what the award was for.

Now let’s put all that into practice and see an example:

Conferences

Conferences represent opportunities for individuals to learn, share their knowledge, and network with other professionals. Therefore, listing them in your data science resume shows dedication and engagement with the community. It’s particularly important to list those conferences where you gave speeches, held presentations, or participated in workshops.

Hobbies & Interests

By mentioning your hobbies and interests, you help recruiters paint a complete picture of who you are as a person beyond your skills and expertise in data science. This section can also differentiate you from other candidates and help you grab recruiters’ attention more easily. Moreover, you can create a personal connection with recruiters and hiring managers by finding common interests.

A great thing about your hobbies and interests is that they don’t have to be related to your profession at all. This is one of the sections where you get to be the real you. If you display a genuine passion for something, it won’t go unnoticed.

On a final note, certain hobbies and interests might imply important qualities about you, such as creativity, curiosity, and problem-solving.

Should You Submit a Cover Letter With Your Data Scientist Resume?

Remember how we mentioned that your resume should be one page long? A cover letter is a perfect opportunity to talk more about your skills and experiences without breaking that rule.

Not only that, but you show commitment and hardworking tendencies by going above and beyond to submit a document that many consider optional and don’t write.

Frequently Asked Questions About Data Scientist Resumes

#1. What should a data scientist put on a resume?

The most important things for data scientists to put on a resume are their work experience, education, and skills. Additionally, they should also include their contact details and a brief introductory paragraph in the form of a resume summary or objective. Finally, they can insert some optional parts, such as certifications, awards, conferences, and more.

#2. What is the best resume format for a data scientist?

In most cases, the best resume format for a data scientist is the chronological resume format. Recruiters are mostly familiar with it and know how to quickly extract a lot of information from such resumes, even by just skimming them for a few seconds. Furthermore, this format is optimized to work well with any type of resume-parsing software.

#3. How do you write an entry-level data scientist resume?

An entry-level data scientist can make up for a potential lack of professional history by writing about their internships, volunteer work, school projects, and similar activities. Additionally, they can emphasize their education section and go in-depth about their academic accomplishments, such as relevant courses, notable achievements, a high GPA, extracurricular activities, clubs, etc.

#4. What skills do data scientists need?

Data scientists often need to have complex skill sets that include many hard and technical skills. Depending on the position you’re applying for, you should mention anything from statistical analysis and computing, machine learning, and deep learning to mathematics and programming on your resume.

Additionally, recruiters often look for candidates with prominent soft skills, such as critical thinking, communication, and problem-solving.

#5. How long should a data scientist resume be?

A data scientist resume should generally be one page long. If you have many years of experience and an extraordinary amount of notable accomplishments to showcase, you can write a two- or even three-page resume. However, the vast majority of candidates should try to fit everything onto one page by being brief and concise and using powerful tools like bullet lists.

Closing Thoughts

Hopefully, writing a catchy and professional data scientist resume doesn’t seem so daunting anymore. You start by following the rules and guidelines closely, and then you can spice things up with a couple of personal touches here and there.

After all, as a data scientist, you’re well aware of the importance of numbers, but you also know that they usually don’t tell the whole story. That’s why it’s crucial to let a bit of your bright and brilliant self through. That way, you’ll be on the road to landing your dream job in no time!