While everyone seems to be looking for data scientists these days, I have been interviewing Analyst and Sr Analyst candidates. The focus lately has been on technical skills and rightly so. Data scientists, for example, need to be able to transform raw data into analysis and actionable insights. That may require experience with Java as well as data mining techniques, an unusual combination.
However, my interviews have reinforced the value of the intangible skills: creativity, commitment, and curiosity. The best candidates provide examples of how they have solved a problem creatively. One candidate described a model he created to deal with missing data. It is rare to have perfectly clean, comprehensive data. Being able to overcome data issues is an important analytic skill.
I also look for candidates who are committed to providing the best possible analysis. Clients pay me to solve difficult problems they can’t solve themselves. They entrust me with their data and I take that trust very seriously. Thus, I want everyone I work with to do the same. While it can be difficult to assess commitment during the interview process, there are telling cues. One candidate asked in advance about her interviewers, came prepared to her interviews with excellent questions that indicated she had researched the company and quickly sent thank you notes after every interview. Her attention to detail and follow through made an excellent impression and spoke louder than words.
I always start an analysis with a hypothesis and a project plan. However, sometimes during the course of an analysis, you find something interesting that changes your plan or analysis. At other times, you may have a hypothesis that turns out to be false when pilot tested. One candidate gave a presentation and at the end admitted that the marketing program she had developed did not generate incremental revenue as expected. I liked that she presented on a program that did not perform as expected. The only way to innovate is to remain curious and willing to test hypotheses.
While technical skills are important, don’t underestimate the intangibles. I can teach someone SAS. It is much harder to teach someone to be curious about data.
