Top Tips and CV Templates for Data Scientists

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In order to get your resume to stand out amongst the stack, there are a lot of things to consider. Even simple choices like what font to use, should you use bold and italics to set off your subheads, job titles, and other features?

Small details make the difference in the eyes of hiring managers, so creating that well-designed standout CV could allow you to leapfrog your competitors and get you to the interview. Obviously creating a functional data science CV is a little more complicated than choosing a font...

The first thing to consider when submitting your CV is to know your audience. If you’re applying directly on a website for a position and the company is medium to large, it’s very likely that your CV will be subject to an Application Tracking System (ATS)

Tailoring your CV to get past ATS.

So, a few things to remember when dealing with ATS.

  1. Your CV will not be seen by a human being if it fails to get past ATS. So even if you are the most talented data scientist in the world, it won’t matter.
  2. Don’t get fancy. Use standard fonts (Arial or Calibri), excessive formatting or decorative elements might present an unreadable mess to the ATS.
  3. Make it keyword-rich, since ATS is looking for keywords specific to the job.
  4. Target the right keywords. If you’re applying for a management position, you’re going to be scored on keywords that are relevant to qualities that are expected of a manager. Review your job spec to find suitable keywords.
  5. Keep it simple, a boring CV that hits all those keywords is far more likely to get past ATS.

However, if you are emailing a recruiter or HR personnel directly than you will be able to get more creative with your CV.

How to create a CV that will grab a hiring managers attention.

Here are the sections we recommend including on every data scientist resume:

  1. Resume Summary or Objective
  2. Experience
  3. Education
  4. Certifications
  5. Skills
  6. Projects
  7. Publications
  8. Hobbies and Interests

Including both an Experience and Projects section will give the recruiter information they are used to seeing, but it also allows you to highlight specific things you’re really proud of working on.

Similarly, a formal Education section and a Certifications section provides you with additional opportunity to showcase knowledge gained. The Publications section will allow you to highlight any articles you've written. With data science roles, you will need you to interact with a variety of audiences, so it’s good to show you can explain ideas in a clear and efficient manner.

A CV or resume is never one size fits all, so use these sections as you see fit.

When it comes to what to the actual writing of your CV then you should check out How to Write a Stand-out CV

Here are a few templates for you to use when creating your data science CV.

data scientist CVdata science cv

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