Data Scientist Resume Template Example

The best resume for a data scientist is in reverse chronological order and formatted, so your most recent career experiences and accomplishments are at the top. Choose a clean, organized template with plenty of white space for readability.

Remember, content is king. Hiring managers can get distracted by busy graphics and fonts. Plus, your template should reflect the type of position you’re seeking and the company’s culture. For instance, if you’re applying for a data scientist position at a buttoned-up organization, you would select a more traditional template than one for an edgy startup. The key is to tailor your resume to the audience.

How To Write a Data Scientist Resume

Tee up your data scientist resume with a concise, dynamic profile that establishes your expertise in a quantifiable way. Your resume also should highlight your career experience, along with including key skills that are essential for succeeding in the field and align with the job description. Additionally, include information about your education and certifications, which shows a commitment to advancing your knowledge in the field.

Following are the essential components of a data scientist resume and some guidance for writing a resume that will stand out among competing candidates.

  • Contact information
  • Profile
  • Key skills
  • Professional experience
  • Education and certifications

Contact information

Include your address, email, and phone number, and a website or LinkedIn profile if you developed an online presence for your career. Your name and contact information should appear at the top of your data scientist resume.

Example:

Your Name
(123) 456-7890
[email protected]
LinkedIn | Portfolio
City, State Abbreviation Zip Code

Profile

A hiring manager will first read your profile to gain a big-picture understanding of your professional experience, skills, and the value you can bring to an organization. This is your elevator speech.

Write a succinct, dynamic resume summary that begins with your job title, years of experience, and three to four specializations that align with the job posting. In the following sentences, illustrate examples of your success. For example, note how you deploy predictive analytics to generate data insights that boost revenues by 15%. Or share how you work collaboratively to communicate complex technical problems in plain language.

Key skills

Data science roles require analytical thinking, experience collaborating cross-functionally with colleagues who are not as technical, as well as statistics and mathematical skills. In the key skills section of your resume, list the hard skills required to perform your job and the soft skills that present you as a team member with strong communication and leadership acumen.

Common hard and soft skills for data scientists

Hard Skills Soft Skills
Data-driven decision making Complex problem-solving
Data visualization Cross-functional collaboration
Natural language processing (NLP) Mentoring
Predictive modeling Team leadership
SQL Translating technical language into simple terms

Resume writer’s tip: Use common action verbs

Action verbs add impact to your experience section, but it’s easy to run short during the resume-building process. In a data science resume, you can also become redundant by overusing words like “analyzed” or “programmed.” When writing your resume, use concise language, avoid the passive voice, and vary your action verbs.

Here is a list of common action verbs for accountant resumes:

  • Collaborated
  • Conducted
  • Created
  • Designed
  • Developed
  • Diagnosed
  • Evaluated
  • Implemented
  • Integrated
  • Managed

Professional experience

Write a success-driven professional experience section with bullet points that emphasize your data science career achievements. Include data, metrics, and monetary figures to demonstrate how your skills deliver value to a company.

Data Scientist, Alpha AI Enterprise, New York, NY
October 2019 – present

  • Collect, analyze, and interpret raw data to develop machine learning concepts that fuel artificial intelligence (AI) initiatives
  • Develop dashboards and reports that deliver insights for data-driven decision-making
  • Evaluated business processes and recommended data science solutions that improved efficiency by 23%, allowing for business development in opportunistic niches
  • Elevated cybersecurity posture and reduced potential for data compromise, mitigating more than 200 attempts during one fiscal year
  • Combined computational linguistics with statistical, machine learning, and deep learning models to inform AI natural language processing

Data Scientist, GoGoTech LLC, Brooklyn, NY
June 2015 – October 2019

  • Spearheaded big data machine learning project that reduced downtime by 23%, freeing up opportunity for business development and revenue growth
  • Developed algorithms to improve system accuracy and security
  • Worked across company teams to gather data and deliver training related to cybersecurity
  • Created a model to accurately predict fraud activity, reducing company losses by 42%

Resume writer’s tip: Quantify your experience

Data, metrics, and monetary figures quantify your experience, so include these measures of your success in your data science resume. Companies are looking for candidates that will drive results and revenue. Illustrate your worth by including examples of specific accomplishments and outcomes. If you launched a machine learning initiative that increased business growth by more than 145%, list this accomplishment upfront.

Check out our example for a better idea of how to do this:

Do

  • Used predictive analytics, including data mining techniques, to forecast company sales with 96% accuracy

Don’t

  • Used predictive analytics

What if you don’t have experience?

If you lack experience in your field, rather than focusing only on skills, your resume should highlight academic projects and industry-related organizations you have served rather than only listing skills. Also, you might opt to write a resume objective section that shares your intentions for advancing your career, showing hiring managers your commitment to professionalism and continuous learning.

Education and certifications

Detail your educational experience by listing the institution and its location, the dates of your time studying science and technology, and the formal name of the degree you earned. If you hold an advanced degree, such as a Master’s in Mathematics, then list this first, followed by your undergraduate degree. If you have certifications such as the IBM Data Science Professional Certificate, be sure to note this in the Education and Certifications section of your resume.

Education

Bachelor of Science (B.S.) Data Science and Analytics, September 2011 – June 2015
Columbia University, New York, NY

Certifications

  • IBM Data Science Professional Certificate, IBM, 2017
  • Google Certified Professional Data Engineer, Google, 2021

Data Science Resume Template Text Example

Your Name

(123) 456-7890
[email protected]
LinkedIn | Portfolio
City, State Abbreviation zip code

Profile

Collaborative, analytical data science professional with seven years of hands-on experience using predictive analytics and classical modeling techniques to generate data insights to drive profitability. Specializes in AI, building models that emulate human intelligence through machine learning. Exemplary programming skills in SQL.

Key Skills

  • AI model building
  • Complex problem-solving
  • Cross-functional collaboration
  • Natural language processing
  • Predictive analytics

Professional Experience

Data Scientist, Alpha AI Enterprise, New York, NY
October 2019 – present

  • Collect, analyze, and interpret raw data to develop machine learning concepts that fuel AI initiatives
  • Develop dashboards and reports that deliver insights for data-driven decision-making
  • Evaluated business processes and recommended data science solutions that improved efficiency by 23%, allowing for business development in opportunistic niches
  • Elevated cybersecurity posture and reduced potential for data compromise, mitigating more than 200 attempts during one fiscal year
  • Combined computational linguistics with statistical, machine learning, and deep learning models to inform AI natural language processing

Data Scientist, GoGoTech LLC, Brooklyn, NY
June 2015 – October 2019

  • Spearheaded big data machine learning project that reduced downtime by 23%, freeing up opportunities for business development and revenue growth
  • Developed algorithms to improve system accuracy and security
  • Worked across company teams to gather data and deliver training related to cybersecurity
  • Created a model to accurately predict fraud activity, reducing company losses by 42%

Education

Bachelor of Science (B.S.) Data Science and Analytics, September 2011 – June 2015
Columbia University, New York, NY

Certifications

  • IBM Data Science Professional Certificate, IBM, 2017
  • Google Certified Professional Data Engineer, Google, 2021