Data Scientist Resume: Examples & Guide for 2025

You don’t want just any data science job. You want one with exciting projects, amazing benefits, and a sky-high salary. To land a job like that, your data science resume needs to show that you’re a true data wizard, able to interrogate dark data hard enough to get all the precious answers.

Give us 7 minutes and you’ll learn how to write a data scientist resume like that.

This guide will show you: 

• A data scientist resume better than most.
• How to ace your data science resume.
• How to write a resume for data scientist that gets the interview.
• Why picking the right data science skills for resumes is the #1 key to get hired.

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Haven't found what you're looking for? Check all our professional resume examples.

From our evaluation of over 500,000 resumes created in our builder, we observed that*:

- The most often added skills by data scientists are Statistical Analysis, Machine Learning, Planning and Coordination, and Data Mining.
- Data scientists, on average, have over 6 years of experience across all their previous jobs.
- Data scientists most often pick our Cascade, Cubic, and Primo resume templates. 
* The data comes from the last 12 months (August 2023-August 2024).

To begin with, see this example of a good data science resume:

Data Scientist Resume Example You Can Copy, Adjust, and Use

Data Scientists are responsible for collecting, analyzing, and interpreting complex datasets. They use statistical principles to develop predictive models and identify patterns and trends in data. With datasets analyzed, data scientists provide insights and solutions to various business problems.

Let’s see a breakdown of what makes this data science resume so great! Plus, you’ll see actionable, step-by-step tips to write an equally stunning one yourself.

1. Use a Professional Data Science Resume Format

As a data scientist, you extract meaning and value from vast sets of complex data. Think about your resume the same way: extract value for your employers.

The first step? Use a clear, legible data scientist resume format. And to make it easier on yourself don't make one from scratch. Pick a visually appealing resume template.

Divide your resume into following sections:

Data Science Resume Template

1. Contact Information
2. Summary or Objective
3. Experience
4. Education
5. Skills
6. Additional Sections

And keep in mind some basic resume formatting rules:

Data Science Resume Format

• Use an elegant resume font.
• Go for single or 1.15 line spacing.
• Set single-inch margins on all sides.
• Make resume section headings larger and in bold.
• List your experience in reverse-chronological order.
• Be generous on white space to avoid that feel of “drowning in data.”
• Make your resume as long as it needs to be. Having a more-than-one-page resume is okay. Skipping important bits about your career isn’t.

Expert Hint: Save your data scientist resume in PDF to keep the formatting intact. But before you send it—double-check with the job ad if PDFs are accepted. Some employers use oldschool ATSs and will allow DOC/DOCX files only.

2. Write a Sparkling Data Scientist Resume Summary or Objective

At the top of your resume, put a carefully crafted resume profile: summary or objective. This is a paragraph of 40–60 words explaining why you’re the perfect candidate for this job.

Think of it as an elevator pitch—a trailer for the rest of your job application.

Got years of relevant data science experience? Pick a resume summary. Showcase your most spectacular accomplishments.

Starting out on your data science career? On an entry-level resume, go for a entry-level data scientist resume objective. Outline what you’ve learned so far and show how well you’d fit in.

Whichever one is right for you, remember about the key thing. Make it about them, not you. Show how your experience and knowledge can translate into their success.

See what I mean:

Data Scientist Resume Example: Summary

Microsoft Certified Data Scientist with 10+ years of experience in Python, R, Java, and Scala. Applied data mining to analyze ABC Inc. procurement processes demonstrating potential savings of $420,000 a year. Seeking to leverage my data visualization and big data modeling skills to help increase XYZ’s investment returns in the upcoming year.

Experienced data science professional with a good working knowledge of Python, R, Java, Scala, Hadoop, SQL, and more. Looking for a challenging data scientist position with independent projects.

The difference is clear. The good example is specific, detailed, and focused on how the candidate will help the employer. Bad example, in turn? All about “me, myself, and I.”

Expert Hint: Although this section comes at the top of your resume, write it last. First, outline your experience, skills, education, and achievements. Then, pick the most impressive bits and fit them into a short-and-sweet summary.

Now, have a look at these two very different data engineer resume objectives for entry-level data science jobs.

Entry-Level Data Scientist Resume Sample: Objective

MSc in Data Science Graduate with 3+ years of internship and freelance experience. Won the 2019 Data Science Fair by building statistical models to predict real estate prices in 8 economic markets with 88% accuracy. Looking to leverage my machine learning and data mining skills to help improve Uber’s model prediction accuracy in the upcoming quarter.

See this? “I’ve learned so much already and I know what you need.”

Fresh Data Science MSc graduate (2018). 3.7 GPA. Not much practical job experience, but I’m a quick learner with exceptional problem-solving and critical-thinking skills. Excelled in data mining coursework.

This one’s actually not awful. But it gives too little proof the candidate can actually do the job.

3. Create Data Science Job Descriptions That Stand Out

Remember Chandler Bing from Friends? He was an IT procurements manager specializing in “statistical analysis and data reconfiguration”—in a way, a nineties’ equivalent of a data scientist.

The problem? His job was so complex and incomprehensible that even his closest friends didn’t know what he did exactly for a living. (Honestly—how many of your friends really understand your job title?)

There’s a lesson to be learned from Chandler. And it applies to your data scientist resume, too.

If you’re applying directly via email to the company you want to join, your resume will most likely reach someone familiar with your niche. But—

If you’re submitting your job application via job boards or online forms, before the hiring manager sees your resume, external recruiters will scan it. Some of them are not tech-savvy enough to understand highly technical descriptions of sophisticated data science projects.

So—Don’t outline every task you handled. To make it easier for them, in your data scientist resume job descriptions focus on the impact your actions had.

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How to List Experience on a Data Science Resume

1. Read the job ad carefully.
2. Jot down resume keywords related to the most important responsibilities and duties.
3. Use those keywords: tailor your resume to the job description.
4. Focus on your achievements instead of listing responsibilities.
5. Enhance each sentence with active verbs: “developed” not “responsible for development.”
6. Add numbers whenever you can.

See what I mean:

Data Scientist Resume Sample: Job Description

Senior Data Scientist
ACB Inc.
Los Angeles, CA
2013–2019

• Developed end-to-end machine learning prototypes and scaled them to run in production environments. Increased efficiency by 23%.
• Contributed meaningful improvements to existing machine learning models through carefully directed research.
• Derived actionable insights from massive data sets with minimal support.
• Provided input into the collection of new data sources and the refinement of existing ones to improve analysis and model development.

Key achievement: Applied data mining to analyze procurement processes resulting in savings of $420,000 a year.

See that? The bottom line is: “I know how to make processess smoother and save company money.”

XYZ Corp.
Data Scientist
2013-2019

• Developing pipelines to analyze large simulation datasets combining own Python, Tcl and Shell scripts with established molecular modeling tools.
• Optimizing factors and designing algorithms for deal recommendations.
• Responsible for the development of audience extension models relying on decision trees, random forest, logistic regression, and other categorical data.

Cool. So you dig data. But that’s already in your job title. What about the actual outcome of your work, huh?

And what if you’ve done a lot of freelancing and have had little full-time contracted experience? Add the “Projects” section below your regular Work Experience.

How to List Projects on a Data Science Resume?

• Describe what you’ve done for a client, what technology you used, and what results you produced.
• If you’re at the beginning of your career and have few projects to choose from, you can include academic projects you had to do for class.
• If you’ve posted your code on Github, add a link to your Github profile in the contact information section.

Expert Hint: If you’re struggling for ideas for good python projects for a resume, browse data science reddit threads. You’ll find tons of inspiration there!

How to Plug Data Scientist Skills to Your Resume?

First of all, do not use generic skills lists. Instead:

• Start with a master list of your data science skill set. Enter all your professional skills, both technical and “soft.”
• Read the job ad carefully and look for skill-related keywords. Mark them.
• How many of the skills expected match those on your master list? Quite a few, right? Presto, that’s your list of skills to put on a resume for data science jobs.

For reference, see the table below:

Data Scientist Skills for a Resume

Hard skills:

• Programming and Software Engineering (include languages you're proficient in)
• Machine Learning, Deep Learning, AI
• Data Visualization
• Linear Algebra
• Data Wrangling
• Data Intuition
• Statistics
• Probability
• Modelling
• Quantitative Analysis

Soft skills:

• Communication (Translating the Tech Language)
• Active Learning
• Problem-Solving
• Critical Thinking
• Judgement
• Perceptiveness
• Risk Analysis
• Inquisitiveness
• Business Intuition
• Collaboration

Here you can find even more technical skills. 

4. Turn Boring Education into a Reason to Hire You

Good news! For experienced data science professionals, putting education on a resume is easy. Include only the highest level of your education.

How to Put Education on a Data Science Resume

List:

• Degree type
• Major
• Minors (if applicable)
• School name
• Graduation date

And that’ll do.

That said—On entry level data science resumes, education should make up for the lack of work experience. If you’re writing an entry-level data scientist resume, elaborate bit more on your college years. Consider including:

• Relevant coursework
• Favorite fields of study
• Academic achievements
• Extracurricular activities

Expert Hint: Don’t include your GPA unless it’s higher than 3.5. Also, if you have more than a year of work experience in your field, skip the GPA altogether.

Entry-Level Data Scientist Resume Sample: Education

BS in Statistics
UCLA
2016

• Excelled in data visualization and machine learning coursework.
• Completed a senior project to predict local companies’ stock values. Used decision trees and regression models.
• Chief editor of the Department of Data Science and Data Modelling Blog between 2014 and 2016.

Wow, who is this? The future Marissa Mayer?!

2016, UCLA, Bachelor of Science in Statistics

• Coursework included: statistical analysis, data science, applied mathematics.
• 3.2 GPA.

That won’t be enough to grab recruiters’ attention. Next please.

5. Spice Up Your Data Scientist Resume With These Extra Sections

The hiring manager is reading your resume for data scientist. She starts to think you’re worth a shot. Whoops. She just changed her mind. What happened?!

She didn’t quite believe the qualifications on your data scientist resume. There was not enough verifiable proof. Want to avoid that bad dream? Include extra resume sections that showcase your unquestionable wins. Provide tangible evidence for your expertise. Check out some ideas:

Extra Sections to Add to a Data Science Resume

• Conferences
• Certifications
• Publications
• Industry awards
• Blogging
• Hackathons participation

Expert Hint: If you have an official certification, add it to your contact details, next to your job title, e.g. Data Scientist, Microsoft Certified.

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Key Points

For a data scientist resume that gets the best jobs:

• Put a summary of your data science qualifications at the top of your resume.
• When describing your data science experience, focus on the results of your actions, don’t get overly technical.
• Focus on showcasing skills relevant to the specific position you’re targeting.
• List your certifications, conferences, awards, and other accomplishments that put you in front of other candidates.

Questions? Concerns? Doubts? Drop me a line in the comments, I’ll do my best to help!

About ResumeLab’s Editorial Process

At ResumeLab, quality is at the crux of our values, supporting our commitment to delivering top-notch career resources. The editorial team of career experts carefully reviews every article in accordance with editorial guidelines, ensuring the high quality and reliability of our content. We actively conduct original research, shedding light on the job market's intricacies and earning recognition from numerous influential news outlets. Our dedication to delivering expert career advice attracts millions of readers to our blog each year.