10 Questions Executives Should Be Asking Before Hiring A Data Scientist Posted on : Nov 21 - 2017

Hiring data scientists is generally considered to be a difficult and time-consuming process. Historically, this has been attributed to a skills gap among applicants and the ever-growing demand from employers. The gap is undoubtedly narrowing due to the proliferation of university programs, bootcamps and MOOC platforms offering rich content from experienced practitioners and luminaries in the field such as Andrew Ng and Peter Norvig. So why is it still so hard to hire a data scientist and demonstrate a return on investment?

Much of the challenge stems from unfamiliarity on behalf of hiring executives. Here are the 10 questions that every executive should be asking before hiring a data scientist:

1. Do You Really Need A Data Scientist?

Unless a legitimate need has arisen (e.g., the business is underperforming or seeking a new competitive advantage), you may not need a data scientist. If there is a need, then you should evaluate simpler methods first such as using heuristics or creating a manual process to address the problem. Just like in elementary school, just because everyone else is doing it doesn’t make it the right decision for your business.

2. Do You Know What You’re Measuring?

Defining the problem and goal beforehand is imperative for proper measurement. For example, a business may want to decrease customer attrition by 10%. In that case, a data scientist could design an experiment by building a model and evaluating the decrease in churn over time against the target.

3. Should You Hire Or Contract?

Generally speaking, hiring makes more sense if the need is long-term and strategic in nature. Data scientist hires also tend to be more successful when there is an established engineering team within the organization. When technology is not a core competency and the objective is a shorter-term nice-to-have, contracting is the way to go. View More