The industry-ready CV or Résumé

… for Data Analytics, Data Science & AI

Chris Armbruster
Jun 18, 2018 · 2 min read

There is a way that you can make your move to Data & AI much more focused: By working with an industry-relevant CV from the start. This means writing a new, second CV that you take with you for your interactions and conversations to collect feedback. Your interlocutors and respondents may much more easily have some of the following for you:

  1. Suggestions of which domains might be interesting and accessible for you.
  2. Network contacts that may be interested in your CV.
  3. A good idea of what the gap (if any) is vis-à-vis your preferred job, and how to close it efficiently.

What do I mean by industry-relevant CV or résumé? A presentation tailored to hiring managers and recruiters or human resources, making it clear just how you and your skills are relevant.

Such a CV is always individual. Still, I can offer the following guidance:

  1. The first page should include your mission and search statement, a technical skills overview, and your last employment.
  2. The second page includes your education, any other employment, and the transferable skills you bring from academia to industry.
Photo by rawpixel on Unsplash

Ad 1) Let’s look at this in some more detail. Your mission and search statement says who you are (e.g. Data Scientist), what you want to do, where you are looking, and why you want to be a Data Scientist.

Next, you should list all technical skills that you are confident of and ready to be tested on. I believe it helps if you indicate your confidence on a simple scale, e.g. a 3-point scale.

I recommend treating your Ph.D. or postdoc position as employment and making the effort to describe it in ways that would be relevant to a hiring manager or human resources department in industry.

Ad 2) When listing your achievements in education you may include any data projects or relevant student jobs you performed. This is to say, I do not recommend listing teaching or student jobs in the employment section, particularly if they were short-term.

However, looking back at your activities and achievements over the past years: Which highly transferable skills have you acquired? Please do ask a search engine for help, and decide which three to five transferable skills you want to list and provide two specific examples for each skill.

Good luck with your transition to data science and AI. Not only do we need more and better talent in this field, but these are also exciting times and the dynamic development of new companies, products, and services will carry us for many years to come.

If you would like to keep up-to-date with the campaign and its workshops, you can do so on Eventbrite, Facebook, or Twitter.

Chris Armbruster

Written by

….find and empower 10,000 Data Scientists in Europe

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