• Chris Armbruster

What is a competency profile?

Updated: May 9

"Substantial, deep expertise in at least one aspect" - since the 2013 landmark study 'Analyzing the Analyzers', we know that these are the most successful practitioners.

Your competency profile shows you are a Senior practitioner (or not yet). The AI Guild supports you in developing your competency profile. For the practitioner, it gives her or his #datacareer a sense of direction. In the best case, you have a professional mission defining the impact you seek. What does that mean?

First, let me iterate on the noteworthy findings from 2013. Second, let us look at the evolving three-fold specialization of the #datacareer by role, industry, and company type. Third, I move from the general to the specific: What does this mean for your competency profile?

The differentiation of data roles

The 2013 study by Sean Murphy, Marck Vaisman, and Harlan Harris provided a summary table on the "mean skill group loadings for survey participants intro four self-identified groups."


Practitioners were asked to self-select a role and self-report their skills. Noteworthy is the validation of the following assumptions:

  • The differentiation of roles as the data businessperson, creative, researcher, or developer.

  • The skillset's breadth with programming, statistics, math (operational research), business, and machine learning.

  • The recognizable profile for each role with specific deep expertise.

  • The complementary nature of the competency profiles overall.

The need for competency profiles

Data roles typically recognized in 2021 are the data analyst, data engineer, data scientist, machine learning engineer, deep learning engineer, NLP practitioner, and computer vision practitioner.

What drives this evolving differentiation of roles is

  • The growth of the field to 1/2 million practitioners

  • Widespread adoption across industries, with specialized use cases becoming dominant

  • Sizeable company teams emerging with specialist roles

It matters whether your computer vision use case is autonomous driving or medical images. It's different when you use your NLP skills for document analysis or a voice-based assistant. Moreover, corporates, startups, and consultancies now have sizeable teams. It makes a difference whether you are a consultant for clients or working on a scalable product, or enabling corporate innovation.

The evolving differentiation means that distinct competency profiles are emerging for the different data roles by the industry and company type.

The personal competency profile

The AI Guild response is working with you on developing and sharpening your competency profile. As roles increasingly are differentiated, you have the unique opportunity to shape your career. As the field is still young, you may achieve the impact you desire.

Here is a suggestion for thinking about your competency profile

  • Did you have a chance to benchmark your data role for the Senior level in your industry and identify any gaps?

  • What deep domain expertise have you acquired already, and where do your real interests lie?

  • Besides honing your technical skills, what other capabilities do you need for your desired impact?

If you like, the AI Guild can support you with your competency profile. You have two options. Firstly, on datacareer.eu, we offer 1-on-1 support in defining your competency profile. Secondly, you can join the AI Guild career development program for long-term support to the Senior level and beyond.

How to get your competency profile?

Are you in Year 2, 3, or 4 of your #datacareer? Would you like to find out how you efficiently show and develop your expertise? It takes 60 days to complete the competency profile. All you need to do to start is point us to your LinkedIn or GitHub profile (or similar) here.

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