The 3 Vectors of Aptitude – How a Balanced Professional Is More Valuable than a Merely Experienced One

Through my role as the CTO of a consulting and recruiting company for data scientists and A.I. professionals, I come across a lot of candidates. Most of the less promising ones are filtered out by my colleague (which is why I still have faith in this field!) so I tend to look at and interview only the ones bound to be more successful. Some of these people are experienced, others not so much (at least not when it comes to industry experience). Yet the ones that stand out, do so, not because they are superstars in one aspect of their professional life (e.g. technical skill-set), but because they maintain a dynamic equilibrium among the various aspects, something that urges them to evolve rapidly and “make stuff happen.”

The factors that I've identified as potentially crucial in predicting a professional’s value in data science and A.I. (and potentially other fields of expertise) are the following:

* Intuition

* Skepticism

* Experience

Let’s look at each one of them more closely.

Intuition

This has to do with the person’s perception and ability to see beyond what’s there, into what could be there and what should be there. Intuition may not be easy to explain, but it is essential, esp. in more advanced positions, where you are expected to think outside the box and provide the organization with novel approaches to tough problems, as well as improvements in the efficiency of existing processes. Intuition is what makes for innovative solutions and enthusiasm in the workplace, though its value goes far beyond all that.

Skepticism

Although this attribute has a bad rep among the more creative people, it is in fact essential in every technical professional. Skepticism involves questioning what you see or experience, and trying to get to the bottom of things. An essential part of the scientific mindset (as well as that of a good journalist), it allows for the methodical refinement of information and the elimination of the BS that floats around the tech pond, and which often evades the management since the people who put it there are very adept at masking everything with trendy buzzwords.

Experience

This is quite well-known, though there is still some misconceptions about how it is gauged. Although it is tempting to represent it as a single number, it is important to differentiate among the different kinds of experience. For example, if someone has been in a start-up for x years, these years don’t contain the same exact experience as x years in a more formal role in a larger organization. Basically, what experience tries to encapsulate is how much has that person learned (actually learned, not just memorized) about the processes that are relevant to their work. Also, if they have gotten some kind of compensation about all this, this validates the quality of the work they've put it, though someone may have gathered equally valuable experience working as an unpaid intern.

It is interesting to examine how these 3 factors correlate and what kind of attributes their various combinations bring about. However, this is best suited as the topic of another article...