Data Scientist Resume Sample—Examples and 25+ Writing Tips

Write a job-winning data science resume with the help of our handy guide. See pitch-perfect data scientist resume sample, get examples and expert tips!

Michael Tomaszewski, CPRW
Michael Tomaszewski, CPRW
Data Scientist Resume Sample—Examples and 25+ Writing Tips

IBM forecast suggests that the amount of all the knowledge in the world will double every 12 hours in 2020. That’s why data scientists are in high demand today. Someone has to process all that data after all!

 

If you’re a data scientist, getting a job will be easy.

 

But you don’t want just any job.

 

You want one with exciting projects, great company culture, amazing benefits, and a sky-high salary.

 

To land *this* job, your data science resume needs to be perfect: 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 resume like that.

 

This guide will show you: 

  • A sample data scientist resume better than most.
  • How to ace your data scientist job description on a resume.
  • How to write a resume for data science jobs that gets the interview.
  • Why picking the right few data scientist qualifications is the #1 key to get hired.

 

data scientist resume example

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

 

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

 

Anne Lounsberry
Data Scientist, Microsoft Certified
523-299-0012
anne.c.lounsberry@gmail.com
linkedin.com/in/annelounsbery12
github.com/annecarollounsberry

 

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.

 

Experience

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.

 

Machine Learning Specialist
AnyCompany
San Diego, CA
2008–2013

  • Collaborated with all team members to optimize Customer Relationship Management database for a high-volume real estate firm.
  • Increased repeat business among real estate investors by 25%.
  • Decreased wasted phone and email time by 57%.
  • Build a machine-learning-based system of matching clients with tailored investment opportunities. Increased customer retention by 30%.

 

Junior Data Analyst
Capgemini
San Diego, CA
2005–2008

  • Consulted and worked with development teams to determine, execute and deliver relevant solutions.
  • Analyzed old information architectures and contributed to the design and development of the new one.
  • Provided information, feedback and guidance to clients to support technology-related decision making.

 

Education

 

MSc in Statistics
UCLA, Los Angeles, CA
2005

Key Skills

 

  • Technical Skills: Machine Learning, Data Visualization, Big Data, Data Mining
  • Programming Languages: Python, R, Java, Scala, PERL
  • Soft Skills: Problem-Solving, Active Learning, Risk Analysis

 

Certifications

 

  • 2014, Google Certified Professional Data Engineer
  • 2008, Microsoft Professional Program Certificate in Data Science

 

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 Template

 

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 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 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 professional big data 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 junior 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.

 

Make an offer.

 

See what I mean:

 

Data Scientist Resume Sample: Summary

GOOD EXAMPLE
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.
BAD EXAMPLE
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, right?

 

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

GOOD EXAMPLE
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.”

BAD EXAMPLE
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 science 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.

 

How to List Experience on a Data Science/Data Modeling 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. Don’t just list data science tasks. Focus on your achievements.
  5. Active verbs are best: “developed” not “responsible for development.”
  6. Use numbers whenever you can.

 

See what I mean:

 

Big Data Resume Sample: Job Description

GOOD EXAMPLE

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.”

BAD EXAMPLE

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 Science 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 data science resume skills section.

 

For reference, see the table below:

 

Data Scientist Qualifications for a Resume

 

Data Science Skills for a Resume
Technical "hard" skillsTransferable "soft" skills
Programming and Software Engineering (include languages you're proficient in)Communication (Translating the Tech Language)
Machine Learning, Deep Learning, AIActive Learning
Data VisualizationProblem-Solving
Linear AlgebraCritical Thinking
Data WranglingJudgement
Data IntuitionPerceptiveness
StatisticsRisk Analysis
ProbabilityInquisitiveness
ModellingBusiness Intuition
Quantitative AnalysisCollaboration

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 a junior 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

GOOD EXAMPLE

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?!

BAD EXAMPLE

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 Modeling Resume With These Extra Sections

 

Nightmare time.

 

The hiring manager is reading your resume. She starts to think you’re worth a shot. Whoops. She just changed her mind.

 

Your resume is in the trash.

 

What happened?!

 

She didn’t quite believe the qualifications on your data science 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

 

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.

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!

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Michael Tomaszewski, CPRW
Michael Tomaszewski, CPRW
Certified Professional Résumé Writer, Career Expert
Michael Tomaszewski is a resume expert and a career advice writer for ResumeLab. He is a certified professional resume writer (CPRW) and a member of the Professional Association of Résumé Writers & Career Coaches. Michael works with candidates across all career stages—from entry-level job seekers to executive coaches. His insights have been featured in CIO and Best Life Online. His mission is to help you tell the story behind your career and reinforce your professional brand by coaching you to create outstanding job application documents. More than one million readers read his career advice every month. For ResumeLab, Michael uses his connections to help you thrive in your career. From fellow career experts and insiders from all industries—LinkedIn strategists, communications consultants, scientists, entrepreneurs, digital nomads, or even FBI agents—to share their unique insights and help you make the most of your career. Michael has a degree in Liberal Arts and specializes in personal and professional storytelling.

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