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Writing a Data Scientist Resume: Do’s and Don’ts

By 2026, the data scientist field is expected to increase by 11.5 million new jobs. Tech giants like Google, Facebook, Amazon, and Apple have entire teams of recruiters looking to find talented data scientists.

Data science is a competitive field and it’s important to have a resume that stands out. According to Indeed.com, a recruiter only spends six to seven seconds reviewing resumes for open positions. Here are some tips to create a memorable data scientist resume.

Showing Experience on a Data Scientist Resume 

Whether you’re looking for an entry level data scientist position or you’ve got 15+ years of experience, recruiters look for a mix of growth, learning new skills and hands-on experience in tools such as statistics, business analytics, machine learning, Python, SQL, data visualization and Tableau.  

While climbing to the top of the data scientist ladder, consider doing an internship to gain practical experience.  You need to practice as employers will require technical tests or test projects as part of the interview process, so be prepared to show your skills. If you don’t have experience and starting out as a data scientist, you can put any projects you’ve done in your education.


Do’s and Don’ts in a Data Scientist Resume 

A great resume tells a story that is targeted to the company’s job description. Stating the number of years of experience you have as a data scientist and summarizing your duties and tasks will help create a complete story.

Recruiters see a LOT of resumes every day, and they use your resume to gauge whether you are a good cultural fit. Here are some do’s and don’ts when writing a data scientist resume.

Do: Create your own resume from template  sites such as Canva, Zety, Indeed, ResumeGenius, or even a Google Doc resume template.
Don’t:  Make your resume complicated with fancy text, layouts or images.

Do: The more senior you are, the shorter your skills section should be. 
Don’t: A one page resume is enough, even for experienced data scientists.

Do: Showcase up at the top of your resume in-demand programs, processes, languages, data sets, and algorithms you’ve worked with.
Don’t: Hide them down at the bottom of the resume, you want them up at the top where recruiters can quickly see.

Do: Check resources like PayScale, Glassdoor, LinkedIn, for insights into the company culture that may be valuable to add to your resume.
Don’t: Putting unnecessary skills that aren’t in the job description.

Do: Use only relevant achievements and include results stated in terms of their quantitative impact.
Don’t: Write a long paragraph, limit each achievement to one sentence.

Do: Quantify your efforts in terms of business impact and context. 
Don’t: Over inflate your metrics. You can give an estimate, you just need to show the recruiters you can contribute to the company.

Do: Network and expand your network as much as possible. Attend data science meetups, join data science learning groups, connect with people in the industry.
Don’t: Give up! It may take some time to land your dream data scientist job.

Acquiring the Skills Needed for a Data Scientist Resume 

Data science careers are in high demand across many fields, and organizations must rely on big data and this is not slowing down any time soon. 

The Udacity School of Data Science offers a range of courses and Nanodegree programs that not only solidify your skills but also provide the opportunity to build a portfolio.

If you’re looking to upskill your data scientist knowledge, enroll in our Data Scientist Nanodegree you can do at your own pace online.

Monique Roberts
Monique Roberts
Monique is part of the Digital Marketing team at Udacity. She enjoys baking, traveling, photography and everything dark chocolate.