Research Summary. We analyzed 1,878 data scientist resumes to determine which ones land the most jobs. Below you'll find examples of resumes that can help you get an interview (and a job offer) from companies like Microsoft and Meta. Here are the key facts about data scientist resumes to help you get the job:

  • The average data scientist resume is 620 words long
  • The average data scientist resume is 1.4 pages long based on 450 words per page.
  • Python is the most common skill found on a data scientist resume. It appears on 13.5% of resumes.
After learning about how to write a professional data scientist resume, you can make sure your resume checks all the boxes with our resume builder.


Data Scientist Resume Example

Choose From 10+ Customizable Data Scientist Resume templates

Zippia allows you to choose from different easy-to-use Data Scientist templates, and provides you with expert advice. Using the templates, you can rest assured that the structure and format of your Data Scientist resume is top notch. Choose a template with the colors, fonts & text sizes that are appropriate for your industry.

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Data Scientist Resume Format And Sections


1. Add Contact Information To Your Data Scientist Resume

Your name should be the biggest text on the page and be at or near the top of the document.

Your address doesn't need to include your street name or house number - listing your city and state works just fine.

Your email address should be professional, but not your current work email address. It's not a good look to use your work email for personal projects (job-searching).

Your social media can be included if you have a fully-fledged LinkedIn page or another social media page that showcases your relevant skill set.

Data Scientist Resume Contact Information Example #1

Hank Rutherford Hill

St. Arlen, Texas | 333-111-2222 |

Do you want to know more?
How To Write The Perfect Resume Header

2. Add Your Relevant Education To The Resume

Your resume's education section should include:

  • The name of your school
  • The date you graduated (Month, Year or Year are both appropriate)
  • The name of your degree
If you graduated more than 15 years ago, you should consider dropping your graduation date to avoid age discrimination.

Optional subsections for your education section include:

  • Academic awards (Dean's List, Latin honors, etc. )
  • GPA (if you're a recent graduate and your GPA was 3.5+)
  • Extra certifications
  • Academic projects (thesis, dissertation, etc.)

Other tips to consider when writing your education section include:

  • If you're a recent graduate, you might opt to place your education section above your experience section
  • The more work experience you get, the shorter your education section should be
  • List your education in reverse chronological order, with your most recent and high-ranking degrees first
  • If you haven't graduated yet, you can include "Expected graduation date" to the entry for that school

Show More

Data Scientist Resume Relevant Education Example #1

Master's Degree In Computer Science 2016 - 2017

New Jersey Institute of Technology Newark, NJ

Data Scientist Resume Relevant Education Example #2

Master's Degree In Computer Science 2016 - 2017

Purdue University West Lafayette, IN


3. Next, Create A Data Scientist Skills Section On Your Resume

Your resume's skills section should include the most important keywords from the job description, as long as you actually have those skills. If you haven't started your job search yet, you can look over resumes to get an idea of what skills are the most important.

Here are some tips to keep in mind when writing your resume's skills section:

  • Include 6-12 skills, in bullet point form
  • List mostly hard skills; soft skills are hard to test
  • Emphasize the skills that are most important for the job
Hard skills are generally more important to hiring managers because they relate to on-the-job knowledge and specific experience with a certain technology or process.

Soft skills are also valuable, as they're highly transferable and make you a great person to work alongside, but they're impossible to prove on a resume.

Example Of Data Scientist Skills For Resume

  • Python Skills

    Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

  • Data Science Skills

    Data science refers to a multidisciplinary discipline that utilizes scientific techniques, procedures, frameworks, and structures to derive information and observations from various organized and irregular data sets.

  • Java Skills

    Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

  • Hadoop Skills

    Hadoop is an open-source software and procedures framework that is free for anyone to use on the internet. Hadoop aids in big data operations. It allows massive data storage, applications to be run on commodity hardware, and can easily manage to run various tasks occurring at the same time.

  • Data Visualization Skills

    Data visualization is the process of presenting data in a more beautiful, elegant, and descriptive way in front of others using visual elements such as charts, graphs, maps, or any other type of visual presentation. This makes the data more natural for the human mind to comprehend and thus makes it easier to spot trends, patterns, and outliers within large data sets.

  • Predictive Models Skills

    In an effort to understand what could happen in the future, predictive models provide the statistical analytics to estimate the possibilities. With predictive modelling, relevant data is collected for the subject that requires forecasting, analysed and modelled to create different outcomes. The importance of this is to provide a basis for decision making that will foster a desired outcome for a business or government.

  • Machine Learning Algorithms Skills

    Machine learning algorithms involve the engines of machine learning. It consists of the algorithms that turn a data set into a model.

Top Skills for a Data Scientist

  • Python, 13.5%
  • Data Science, 9.9%
  • Visualization, 5.3%
  • Java, 4.5%
  • Other Skills, 66.8%
Not sure which skills are really important?
3 Big Tips For Listing Skills On Your Resume

4. List Your Data Scientist Experience

The most important part of any resume is the experience section. Recruiters and hiring managers expect to see your experience listed in reverse chronological order, meaning that you should begin with your most recent experience and then work backwards.

Don't just list your job duties below each job entry. Instead, make sure most of your bullet points discuss impressive achievements from your past positions. Whenever you can, use numbers to contextualize your accomplishments for the hiring manager reading your resume.

It's okay if you can't include exact percentages or dollar figures. There's a big difference even between saying "Managed a team of engineers" and "Managed a team of 6 engineers over a 9-month project."

Most importantly, make sure that the experience you include is relevant to the job you're applying for. Use the job description to ensure that each bullet point on your resume is appropriate and helpful.

What Experience Really Stands Out On Data Scientist Resumes?

Earvin Balderama Ph.D.

Assistant Professor of Statistics, California State University, Fresno

What really stands out on a resume are research projects, especially ones that are outside of the normal curriculum. Sometimes, applicants talk about a particular project, from beginning to end, for an entire interview session, and they get the job because of it. Managers are usually impressed when an applicant can explain their thought process as they struggled through a project because it mimics what will happen in the real world. Students should definitely seek out independent research opportunities while they're in school. Show more

Don't have any experience?
How To Show Your Experience On a Resume... Even When You Don't Have Any
Work History Example # 1
Logistics Coordinator
  • Coordinated efforts within the area to ensure the timely and efficient turn of freight through the facility.
  • Provided employees and subordinate supervisors with direction and advice regarding policies, procedures, and guidelines.
  • Consolidated and communicated process of return authorizations between carriers and warehouses using TMS and GERP systems.
  • Maintained ERP inventory system to provide accurate information for sales and customer service departments.
  • Created the first USCS enterprise wide integrated systems concept.
Work History Example # 2
Data Engineer
  • Created the tables in Hive and written data in using Talend hive components.
  • Streamed real time data by integrating Spark with Kafka for dynamic price surging.
  • Involved in transfer of data from post log tables into HDFS and Hive using SQOOP.
  • Designed Teradata BTQ scripts to move high volumes (> 100 million records daily) of data.
  • Diagnosed and produced solutions to problems such as scalability to thousands of processing units and load balancing on terabytes of data.
Work History Example # 3
Data Scientist
  • Consolidated 5 regional billing applications and increased business efficiency of business software sales.
  • Hired to solve tough high level problems with low level analytics.
  • Streamlined existing processes to increase timeliness and decrease errors; developed PowerPoint presentations and communicated weekly dashboard status to management.
  • Improved curriculum materials in python, machine learning and statistical inference.
  • Implemented HTTP requests to call the specific API using the python libraries.
Work History Example # 4
Quantitative Analyst
Nationstar Mortgage
  • Modeled exotic options like volatility/variance swap and dual currency deposits.
  • Developed and implemented firm-wide global and domestic equity, and global fixed income performance attribution systems.
  • Updated data templates with Barclays POINT and Bloomberg.
  • Performed data mining and statistical analysis on loan performance using SQL and R. Visualized loan performance and effects of different factors.
  • Revamped the analytics framework in Python

5. Highlight Your Data Scientist Certifications On Resume

Certifications can be a powerful tool to show employers that you know your stuff. If you have any of these certifications, make sure to put them on your data scientist resume:

  1. Associate - Data Science Version 2.0
  2. AWS Certified Machine Learning – Specialty
  3. IBM Certified Data Engineer - Big Data


6. Finally, Add a Data Scientist Resume Summary Or Objective Statement

A resume summary statement is a 1-3 sentence spiel at the top of your resume that quickly summarizes who you are and what you have to offer. In this section, include your job title, years of experience (if it's 3+), and an impressive accomplishment, if you have space for it.

Remember to address skills and experiences that are emphasized in the job description.

Are you a recent grad?
Read our guide on how to write a resume summary statement

And If You’re Looking for a Job, Here Are the Five Top Employers Hiring Now:

  1. Airbnb Jobs (216)
  2. Meta Jobs (1,734)
  3. Apple Jobs (314)
  4. Lyft Jobs (150)
  5. Google Jobs (392)

Common Data Scientist Resume Skills

  • Python
  • Data Science
  • Visualization
  • Java
  • Hadoop
  • Tableau
  • Data Analytics
  • Data Visualization
  • TensorFlow
  • Machine Learning Techniques
  • Predictive Models
  • Machine Learning Algorithms
  • Neural Networks
  • Scala
  • Machine Learning Models
  • SAS
  • Statistical Analysis
  • Natural Language Processing
  • AWS
  • Pandas
  • Scikit-learn
  • Data Collection
  • Keras
  • Math
  • Predictive Analytics
  • Regression
  • Power Bi
  • B Testing
  • Text Mining
  • Statistical Methods
  • Statistical Models
  • Azure
  • Time Series Analysis
  • NumPy
  • Decision Trees
  • Extraction
  • ETL
  • Linux
  • NoSQL
  • GIT
  • A/B
  • Exploratory Data Analysis
  • BI
  • Logistic Regression
  • Strong Analytical
  • Patients
  • Cloud Computing
  • SPSS

Data Scientist Jobs