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Data Scientist Resume: Examples & Guide (Also Entry Level)

Data Scientist Resume: Examples & Guide (Also Entry Level)

You’re the person who transforms lumps of data into eye-opening insights. Here’s how to apply your skills and create a compelling data scientist resume that stands out.

Remember the time when the Harvard Business Review published an article titled “Data Scientist: The Sexiest Job of the 21st Century”?

 

So you’ve studied hard to get into the coveted field of data science. You can wrangle the toughest, messiest data set into a bunch of neat diagrams and actionable insights. So where are all those companies that should be fighting over the right to hire you?

 

Well, those companies don’t even know how great you are. You have to take the first step and impress them with a resume that tells a clear story of your awesomeness.

 

Fortunately, you won’t have to analyze half a million resumes to uncover the resume writing tips that actually work. Just sit back and read this step-by-step guide.

 

This guide will show you: 

 

  • A data scientist resume example better than 9 out of 10 other resumes.
  • How to write a data scientist resume that will land you more interviews.
  • Tips and examples of how to put skills and achievements on a data scientist resume.
  • How to describe your experience on a resume for a data scientist to get any job you want.

 

Want to save time and have your resume ready in 5 minutes? Try our resume builder. It’s fast and easy to use. Plus, you’ll get ready-made content to add with one click. See 20+ resume templates and create your resume here.

 

Create your resume now

 

data scientist resume example
data scientist resume example

Data scientist resume made in our builder—See more resume templates here.

 

Data Scientist Resume Example

 

Linda Hedrick

Data Scientist

416-938-5739

lindahedrick@email.com

www.linkedin.com/in/lindahedrick

 

Summary

 

Insightful, detail-oriented data scientist with 8 years of experience. Eager to support Pixadrive Inc. in optimizing costs and boosting revenue. Achieved a $30,000 increase in company revenue and a 10% increase in customer retention.

 

Experience

 

Data Scientist

DarpanDiesen, Vancouver, BC

July 2018–January 2022

Key Qualifications & Responsibilities

  • Built a predictive model that estimated the chance of equipment failure with 25% more precision than the model used previously
  • Analyzed production processes with custom machine learning algorithms to generate $20,000 in savings
  • Reduced data processing time by 80% by improving the functionality of reporting dashboards
  • Used data-driven insights to reduce transportation costs

Key Achievement: 

  • Implemented a series of pricing experiments that led to a $30,000 increase in revenue

 

Junior Data Analyst

Cloudtriq, Victoria, BC

September 2015–June 2018

Key Qualifications & Responsibilities

  • Researched marketing trends and provided the company with actionable insights that led to the successful launch of a new product
  • Assisted senior data scientists in analysis that increased sales performance by 20%

Key Achievement: 

  • Analyzed customer survey data and proposed CX improvements that increased customer retention by 10%

 

Data Science Intern

Ymetrics, Toronto, ON

November 2014–April 2015

Key Qualifications & Responsibilities

  • Assessed data quality and cleansed data for further processing
  • Provided actionable insights for business improvements

 

Education

 

Master of Science in Applied Computing (MScAC)

University of Toronto, Toronto, ON

Graduated in 2015

Concentration in Data Science

 

Bachelor of Science 

University of Toronto, Toronto, ON

Graduated in 2013

Specialization: Data Science

 

Skills

 

  • R
  • Python
  • Hadoop
  • MySQL
  • Data visualization
  • Predictive modelling
  • Machine learning
  • Critical thinking
  • Problem solving
  • Decision-making

 

Certifications

 

  • Microsoft Professional Program for Data Science, Microsoft, 2015
  • Cloudera Certified Professional: Data Scientist, Cloudera, 2016

 

Hobbies

 

  • Chess
  • Writing sci-fi fiction

 

Now, here’s our data-driven, actionable, step-by-step method for crafting a data scientist resume.

 

1. Structure Your Resume Strategically

 

You know how the right data visualization technique can instantly transform a few hundred thousand rows of data into a crystal-clear picture.

 

It’s the same with writing your resume. 

 

Provide recruiters with an overview of your career that clearly highlights your strengths and tells a story of success.

 

Here’s how to do it.

 

When describing your work experience and educational background, your safest bet is opting for the so-called reverse-chronological format. This is a resume layout where you start with your most recent achievements and end with the humble beginnings of your career.

 

But before you dive into that, start with a resume header that catches the recruiter’s eye and presents your name and contact information. This ensures that the recruiter won’t have to search for your email address when they decide to invite you to the interview!

 

Remember that your resume header should only include your name and contact information. Avoid putting things like your date of birth or marital status in the resume. While this information is surely important to you, it interferes with the clarity of the data you’re presenting to the recruiter.

 

OK, the header is pretty obvious. But how do you structure the rest of your resume?

 

As with presenting any kind of data, clarity is key. Divide your resume into sections and give each section a big, easy-to-read heading. Don’t skimp on whitespace around the headings. 

 

Here are the sections you should include in your data scientist resume:

 

  • Header with contact info
  • Summary Statement/Career Objective
  • Work Experience
  • Education
  • Skills
  • Additional Sections (Conferences, Extra Training, Volunteering, Certifications, Etc.)

 

But before you start filling out the sections, there’s one more thing to think about: readability. Use classic, easy-to-read fonts, set the line spacing to 1.15, and make sure there are even margins on all sides.

 

Also, save your resume as a PDF file so that your carefully crafted resume layout won’t turn into a train wreck when opened on another computer.

 

Please remember: some job adverts explicitly ask you to submit your resume as a Word document. If that’s the case, do so. Not all applicant tracking systems can read PDF files.

 

Good. Now that we’ve talked about formatting, it’s time to take a deep dive into each section. We’ll skip the summary statement/career objective section for now, but don’t worry. We’ll get back to it later on.

 

Read more about picking the best resume layout for your needs.

 

2. Provide All The Data About Your Work Experience

 

Your work experience is arguably the most important section of your resume

 

This is why you have to make sure your employment history delivers an unforgettable “aha moment” and makes the recruiter want to send out that interview invitation.

 

But how do you present your work experience as an exciting success story, not just as a set of boring raw data (worked there, done that…)?

 

Present your career in reverse-chronological order. This means you start with your most recent work experience and go backwards in time.

 

Deliver no incomplete data. Make sure each entry in your work experience section contains your job title, the company name and location, and the months and years when you started and left.

 

Condense your achievements and responsibilities in up to 6 bullet points per employer. If you come up with more than six bullet points, you’re probably trying to include some really trivial details, like “responsible for making coffee”. If you’ve got too few, the recruiter might think you haven’t accomplished anything worth mentioning.

 

Collect data from the job advert. Look for keywords that describe specific job requirements and include them in your resume. If the employer wants someone who can “implement cutting-edge predictive analytics solutions in multiple areas of business”, make sure your resume mentions how you managed to implement a predictive analytics solution that made business metrics skyrocket. Yes, recruiters and applicant tracking systems really pay attention to this.

 

Highlight measurable achievements, not duties and responsibilities. If you write that you were responsible for writing scripts, the recruiter will just sigh and pick up the next resume. Being responsible for something doesn’t necessarily mean you did it well.

 

Just like that person who was responsible for letting the Trojan horse in, you know.

 

Instead, rest assured that recruiters love metrics and numbers as much as you do. You didn’t just stare at a petabyte of data until it revealed its secrets. You gained data-driven insights that reduced production costs by 10%

 

Use a proven formula for writing bullet points. You know that formulas can do wonders if used correctly. So here’s one for you: P - A - R, which stands for Problem - Action - Result (or Project - Action - Result).

 

Here’s how you apply it:

 

Start each bullet point with a powerful verb (Action), state what you were working on and then present the results, preferably with a nice little bit of data included.

 

Like this:

 

Predicted (action) stock price (project) 25% better than traditional methods (result).

 

Now let’s look at some more examples.

 

Data Scientist Resume Template: Work Experience

RIGHT

Data Scientist

DarpanDiesen, Vancouver, BC

July 2018–January 2022

Key Qualifications & Responsibilities

  • Built a predictive model that estimated the chance of equipment failure with 25% more precision than the model used previously
  • Analyzed production processes with custom machine learning algorithms to generate $20,000 in savings
  • Reduced data processing time by 80% by improving the functionality of reporting dashboards
  • Used data-driven insights to reduce transportation costs by 10%

Key Achievement: 

  • Implemented a series of pricing experiments that led to a $30,000 increase in revenue
WRONG

DarpanDiesen, 2018–2022

Data scientist

  • Analyzed data from the factory floor
  • Developed a custom machine learning algorithm
  • Responsible for improving reporting dashboards
  • Helped the marketing team decide on product prices

How would you estimate the second candidate’s chances of landing an interview?

 

Before you shout “Zero!”... 

 

…realize that both samples come from the same candidate.

 

The first sample shows precisely how her data-driven insights helped boost the company’s crucial business metrics. Anyone who reads it will think, “Well, if she helped increase per previous employer’s revenue by $30,000, she could do the same for us, so let’s hire her!”

 

The second sample describes the same job experience. However, all it says is, “I did some data-sciencey things, and I can also spell the word algorithm.” You can’t even tell if the candidate’s data science skills brought considerable benefits to the company. So why hire someone who just sits at a computer and crunches numbers without any real use?

 

Alright, but what if you don’t have any epic achievements to show off because you’re just starting out? How do you put all those measurable successes and power words into an entry-level data scientist resume?

 

Here’s how.

 

Entry-Level Data Scientist Resume: Examples

RIGHT

Data Science Intern 

Cosmetixe, Ottawa, ON

January 2020–June 2020

  • Reduced the time spent on sales reports by 20% by implementing data analysis tools
  • Assisted in developing a product recommendation engine that led to a 10% increase in average order value 
  • Leveraged 10,000 tweets to develop a sentiment analysis model that informed the company’s marketing strategy and helped increase customer satisfaction by 5%
WRONG

Cosmetixe, 2020

Data Science Intern

  • Did some coding in Python to analyze sales data
  • Implemented machine learning algorithms for our online store
  • Analyzed tweets about our brand to help the marketing department

See what the candidate did in the first sample? Despite being “just” an intern, they clearly showed that they participated in successful projects that brought clear benefits to the company.

 

The second sample is… just meh. First, you never know how long the internship lasted. Maybe the person only spent two weeks at the company before getting fired?

 

Second, the bullet points don’t show that the intern’s activities were of any actual use. “OK, you did some coding in Python. So what?”

 

When making a resume in our builder, drag & drop bullet points, skills, and auto-fill the boring stuff. Spell check? Check. Start building a professional resume template here for free.

 

When you’re done, Zety’s resume builder will score your resume and tell you exactly how to make it better.

3. Showcase Your Education

 

Because so many people complete a $3.99 course on Udemy and call themselves data scientists, recruiters are wary and pay close attention to candidates’ educational credentials.

 

Proudly displaying your education in your resume will create trust and convince recruiters that you actually know what you’re doing.

 

But how much should you write, and how far back should you go?

 

Well, it depends on how much work experience you have.

 

If you have serious professional achievements to speak for you, don’t go into too much detail about your studies. Just list your highest degree of education.

 

If you’re a fresh graduate just starting out in the data science field, add more information about each degree. Mention some of the courses you did or the projects you completed.

 

But in any case: if you have a degree, don’t mention your high school.

 

Education on a Data Scientist Resume: Examples

RIGHT

Master of Science in Applied Computing (MScAC)

University of Toronto, Toronto, ON

Graduated in 2015

 

Concentration in Data Science

WRONG

Uni Toronto, MScAC

 

Pear Tree School, Vancouver

Won 1st prize for science project in 6th grade

A 6th grade science project? No. One. Cares.

 

What would an entry-level data scientist put on their resume, then?

 

Junior Data Scientist Resume: Education

RIGHT

Master of Science in Computer Science (MSc)

The University of British Columbia, Vancouver, BC

Graduated in 2022

  • Completed a senior project to predict coffee prices using neural networks (LSTM & RNN)
  • 3.7 GPA 

 

Bachelor of Science in Computer Science (BSc)

The University of British Columbia, Vancouver, BC

Graduated in 2020

  • Excelled in machine learning and algorithm design courses
  • Completed small-scale projects in the fields of e-commerce and AI 

4. Present Your Skills Like a Data Pro

 

Now’s the time for the skills section of your resume. Writing it is as simple as mining a little chunk of data.

 

When the applicant tracking system reads your resume, it’s going to look for the same skills-related keywords that appeared in the original job advert.

 

So get back to the job ad and extract all the skills mentioned there. You don’t need to write a script to do it - just go through the text and highlight anything that looks like a skill.

 

Now make a separate list of your professional skills. Not what the employer wants, just what you can do. But remember that having written a “Hello world!” script in a specific language doesn’t make you skilled in it!

 

After you’ve extracted and prepared this data, it’s time for some analysis. Compare the two lists and see which of your skills match the job ad. Those are the skills that go on your resume. There’s probably going to be 5–10 of them.

 

But don’t stop there. Get back to your education and work experience sections. Could you rephrase some of the bullet points so that they mention specific skills? By all means, go for it - having an even distribution of skill-related keywords makes your resume look more consistent.

 

Data Scientist Skills to Put on Your Resume

 

Here’s a list that you can draw inspiration from.

 

HARD SKILLS

 

  • Data Analysis
  • Statistics
  • Data Visualization
  • Quantitative Analysis
  • Machine Learning
  • Modelling
  • Mathematics
  • Probability
  • Debugging
  • Programming
  • Data wrangling

 

SOFT SKILLS

 

  • Research
  • Critical Thinking
  • Communication
  • Time-Management
  • Generating Hypotheses
  • Executing in a Fast-Paced Environment

 

TECHNICAL SKILLS

 

  • R
  • Python
  • C++
  • C#
  • Java
  • JavaScript
  • PHP
  • SAS
  • SQL
  • Scala
  • MATLAB
  • Hadoop
  • OpenRefine
  • Cloudera
  • Tableau
  • Microsoft Excel
  • Spark
  • PowerBI
  • AWS

 

Now let’s look at a real-world example.

 

Data Scientist Resume: Sample Skills Section

RIGHT

Skills

 

  • R
  • Python
  • Hadoop
  • MySQL
  • Data visualization
  • Predictive modelling
  • Machine learning
  • Critical thinking
  • Problem-solving
  • Decision-making

5. Enhance Your Resume With Extras

 

By now, you may be wondering where you could brag about your certifications, awards, and other achievements like speaking at data science conferences.

 

Well, make extra sections! Just make sure you only include relevant extras—most employers looking for a data scientist probably won’t care whether you’re also a certified Baby Shower Party Planner.

 

If you’re a junior data scientist, you can also include academic awards and volunteering activities. 

 

What about hobbies and interests? They can give your resume a nice personal touch and highlight your skills. If your potential employer is looking for a “team player”, you can mention that you play basketball.

 

Just don’t write anything that’s too weird, like kitten taxidermy or collecting books about serial killers.

 

Data Scientist Resume Sample: Extra Sections

 

Here’s how a data scientist could describe their certifications and hobbies:

RIGHT

Certifications

 

  • Microsoft Professional Program for Data Science, Microsoft, 2015
  • Cloudera Certified Professional: Data Scientist, Cloudera, 2016

 

Hobbies

 

  • Chess
  • Writing sci-fi fiction

You can see they only featured their certifications in data science (though they might also be a certified Pokémon Professor). The candidate also chose to mention hobbies that highlight relevant skills such as critical thinking, problem-solving, and researching.

 

6. Present the Most Convincing Data About You in Your Resume Summary or Objective

 

Now’s finally the time for the resume section that goes right after the header.

 

This is where you write a short, catchy summary of your career. And if you’re a junior data scientist and don’t have much to summarize, you use the top section to state your objectives instead.

 

Why should you write this section last?

 

Let’s look at it this way.

 

When you want to make a decision, you like to have all the relevant data right in front of you, don’t you?

 

That’s why it’s good to have all of your achievements and skills neatly listed on a page before you decide to highlight specific points in your summary or objective.

 

Now that you’re ready with all the other sections of your resume, let’s get down to the summary (or objective). Here’s how to write it:

  • Take a close look at your resume. Look for achievements and skills that are particularly impressive and relevant to the job ad.
  • Paste your newly found nuggets of data into the following formula: Adjective + Job Title + Years of Experience + Achievements + Skills + How You Want To Help Your Employer Achieve Their Goals. You’ll end up with 2-5 sentences.
  • Edit your summary/objective until it’s powerful and catchy.

 

Not sure what makes a good resume summary? Take a look at these examples.

 

Data Scientist Resume Examples: Summary

RIGHT

Insightful, detail-oriented data scientist with 8 years of experience. Eager to support Pixadrive Inc. in optimizing costs and boosting revenue. Achieved a $30,000 increase in company revenue and a 10% increase in customer retention.

WRONG

Data scientist looking for new challenges. Worked for a manufacturing company and a software house. Loves coding and playing chess.

Can you see how the second example is wrong on so many levels? It highlights some pretty irrelevant information (like playing chess) and doesn’t show how hiring this person will benefit the employer.

 

Let’s look at some resume objectives for entry-level data analysts.

 

Entry Level Data Scientist Resume Sample: Objectives

RIGHT

Data science graduate with 5 successfully completed projects. Seeking to support decision-making processes at Pixadrive Inc. with data mining and analysis.

This candidate may not have breathtaking achievements yet, but they’re eager to put their skills to good use and help their employer make better business decisions. Sounds good.

WRONG

New graduate looking for a machine learning job. Eager to crunch some numbers, practice Python, and learn new things.

Guess what? You don’t have to write that you’re looking a job. If you weren’t, you wouldn’t bother to apply for it.

 

Oh, and no employer wants you to “practice” on their valuable data. There’s Kaggle for this.

 

7. Complement Your Resume with a Cover Letter

 

Now that you’ve spent a few hours working on your resume, the thought of writing a cover letter might feel daunting. Does anyone even read them now?

 

Well, some employers don’t. But many do. And quite a lot of recruiters reject resumes that don’t have a cover letter attached.

 

It’s better to be safe than sorry, so just go for the extra effort.

 

After all, you don’t want your perfect resume to land in the trash just because you didn’t include a cover letter!

 

Even if your prospective employer doesn’t require a cover letter, they’ll still appreciate the fact that you wrote it. And it might give you a competitive edge over hundreds of others similarly skilled candidates.

 

So… how do you write a cover letter?

 

All you need to do is follow these simple steps:

 

  • Create a well-formatted cover letter header
  • Grab the reader’s attention with a catchy opening paragraph that highlights your achievements
  • Show why you're the best fit for the company
  • Explain why you want to work for this particular company
  • End with a powerful call to action

 

A great cover letter that matches your resume will give you an advantage over other candidates. You can write it in our cover letter builder here. Here's what it may look like:

 

See more cover letter templates and start writing.

Key Takeaways

 

Here’s how to write a data scientist resume step by step:

 

  • Pick a time-proven formula for structuring your resume
  • Describe your work experience, focusing on measurable achievements
  • Show that you’re qualified for the job by presenting your education
  • Add extra sections to help recruiters visualize your awesomeness in its full glory
  • Sum up the most important data and write a catchy resume summary (or resume objective)
  • Maximize your chances of success with a cover letter

 

Thanks for reading my guide! Now I’d love to hear from you: 

 

  • What are the biggest challenges of writing a sales associate resume? 
  • What part do you struggle with the most? 

 

Let me know. Let’s get the discussion started!

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Jamie S. Marshall
Jamie is a career expert who has worked with job-seekers from all walks of life. At Zety, he helps readers write successful job applications and land their dream jobs.

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