Back

 Industry News Details

 
Key Qualities To Look For In AI And Machine Learning Experts Posted on : Nov 22 - 2017

Recruiting machine learning (ML) talent is different than for traditional software development. The field of artificial intelligence is so young that it can be difficult to parse candidates by their background and experience alone. Instead, hiring managers should look for certain skills and qualities that are particularly valuable for machine learning projects, many of which are highly exploratory and experimental. While there are many different artificial intelligence job titles, these are the overall qualities to look for in when hiring for AI teams.

A solid background in mathematics and statistics is helpful in traditional software engineering but is mandatory for work in machine learning. Fred Sadaghiani CTO of Sift Science, said, “We are looking primarily for people who have a principled understanding of the statistics, probabilities, and math necessary to grasp the problem. That’s the foundation of this all.” This fundamental knowledge allows machine learning engineers to understand which algorithms best address a problem and how to optimize outcomes.

While many graduates have the prerequisite mathematical foundation, more nuanced character traits truly distinguish top candidates. Look for individuals with an innate curiosity and creativity to excel in the field. They are the ones best able to grapple with abstract information and deduce novel ways to approach problems especially common in machine learning. According to Sadaghiani, “a good machine learning person is a curious person, is somebody who can be creative, is somebody who can take an extremely abstract unclear problem and bring to light clarity around the possibilities.”

The ability to understand data and derive meaning is also useful. While data scientists are often paired with business analysts, it's essential that they also understand the applied implications of their research. Jenny Dearborn, SAP's chief learning officer, noted that "[We're not always looking for] the right answer, but what is the right question to ask. What is the insight, meaning and purpose of the analysis that was overlaid on the data?"

Machine learning research is a new field and few projects are easy. It can take many months and countless iterations to achieve accurate results. Good researchers have perseverance and a relentless drive to seek answers. Explains Cole Shiflett, head of people operations at ThoughtSpot, “we’re really looking for people who have capacity; who have the commitment to having an impact in the space and engaging with the big questions around AI.” View More