Data scientist CV examples for this year

A professional CV is critical for data science job applications. Use CVHelp for their CV examples!



Table of Contents

  1. Data scientist CV examples
  2. What Is a data scientist CV?
  3. What to include in data science CVs
  4. Data scientist CV sample
  5. FAQ: Data scientist CV examples

Data scientist CV examples

Data scientists must be adept in many different skill sets. Not only do they need to understand data sets and algorithms, but they are required to be proficient at data visualization using tools such as Python and SQL.

Having a strong CV will help you stand out to recruiters for jobs in this field, including data analysis, data modeling, and other data scientist jobs. CVHelp can get you there with CV examples based on your industry!

What Is a data scientist CV?

The bulk of a data scientist CV should present your accumulation of work experience, skills and certifications. Not only does it show your years of experience, but it also demonstrates to the hiring manager the metrics of your qualifications to be a data scientist.

What to include in data science CVs

Data science CVs should follow the typical professional CV format unless otherwise stated in the job description or by the recruiter. CVHelp has various CV templates available based on your industry of interest.

There are five key sections that you must include in your CV: your contact information, a professional summary section, an experience section, a skills section, and an education section.

1. Contact information

Your contact information should include your full name, phone number, and address. You can also include professional online profiles, such as LinkedIn.

2. Professional summary

This section should be a strong introduction to your background and skills, all within a few sentences. It can be particularly good for highlighting your biggest strengths and even listing certifications. Think of this as a sales pitch, where you are pitching your value to recruiters.

3. Experience section

Keep this section relevant to what your recruiters are looking for in the job description. In addition to professional experiences, you can also include related activities such as research or start-up opportunities, data science projects, and certifications.

In addition to this, quantify your experiences. How long have you been working here? How many people did you work with? How many data sets have you dealt with? Have you helped tackle any business problems using your proficiency in data science? Provide details about your experience, but keep it concise.

4. Skills section

Your skills section is one of the most important items on your CV, next to your work experience. This section should be written in bullet points, not listed out as sentences.

It is good to include both soft skills and technical skills in this list. Technical skills can be practical skills, such as “analyzing data algorithms”. Soft skills are interpersonal skills that can speak to your personal qualities, such as problem-solving and critical thinking. Remember that relevance to the industry is key.

5. Education section

Your education section should include your highest education credential, whether it’s secondary school or college-level education. If you are currently a student, you can include an expected graduation year.

Data scientist CV sample

The following is a data scientist CV example. The content may vary depending on what the hiring manager is looking for. If you are having trouble starting your CV, use this sample for inspiration. CVHelp can also help you craft your perfect CV with our online CV builder.

Jane Doe

078 4982 6538

Newton, UK

Graduate student seeking opportunities to work with large sets of data and data analytics. Aim to aid business models with data mining and interpretation, with an end goal on becoming a data engineer.


  • Data mining
  • Data analysis
  • GitHub machine learning models
  • Organizing and interpreting data sets
  • Proficient in Python, Java, SQL, and Hadoop
  • Sifting and combining big data sources for research reports
  • Problem-solving

Work Experience

Data Scientist

Datastic, Newton, UK 2018-2020

  • Conducted data regression analyses of the relationship between house prices and house size
  • Managed hundreds of data sets, including competitor data and real-time changes to the house market prices
  • Utilised data regressions for predictive modeling of future house prices relative to house size
  • Routinely used Hadoop for large data computations


University of Newton 2017-2021

Bachelor of Computer Science


Microsoft Certified Solutions Expert

FAQ: Data scientist CV examples

Q: What skills should I include in a data science CV?

The main takeaway for any skills section in a CV is relevancy. You want to ensure that you are not just showing off a bunch of skills that you have accumulated over time. Keep your skill section list narrowed to the most critical abilities that apply to your desired job.

You can look at other related data science CVs and job postings for inspiration. Try to think of what hiring managers are looking for. Some examples of relevant data science skills are:

  • Data visualisation
  • Data mining algorithms
  • Programming languages (such as Python and Java)
  • SQL
  • Data modelling

Q: Should I include courses in my CV?

You can most certainly include courses in your CV if you feel it would give you a leg up on the competition. However, unless you were involved in unique studies, including your top education credentials and experiences speaks more to recruiters than a list of courses.

Most people seeking data science jobs have taken many computer sciences, data modeling, statistics, and programming classes, but it’s better off featuring them on a separate linked profile, such as your LinkedIn page.

Q: Do data scientist jobs require cover letters?

Many jobs this year require cover letters as part of the application. It never hurts to include a cover letter for your job. CVHelp can help you get started on your cover letter with our cover letter builder and examples!


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