Most interviewers always aim to recruit all-rounded employees. For instance, to employ the right data scientist requires a specific set of questions while interviewing them. Fortunately, there are numerous interview questions from different sources despite most of them tend to incline on the technical and quantitative facets of the job with less or no considerations to other softer skills a data scientist may have.
Because of that, it is key to take a different tactic while interviewing data scientists. Focusing on more than the technical questions is the way to go. Data scientists also possess exceptional sets of skills since they do not only solve data problems by mining data but also should have necessary skills to communicate their results, in addition to, managing to convince the right stakeholders to apply such information in their decision-making process. While interviewing data scientists, an interviewer should be able to spot skills such as logical reasoning ability together with storyboarding skills since such skills are dire because they are needed in solving problems iteratively, in conjunction with other business analysts and decision makers in an organization.
To better interview data scientists, interviewers should be able to structure their questions into the following three categories and put equal emphasis to each of the categories;
While interviewing on this question category, interviewers should keep in mind that they are looking for statistics and machine learning skills in all data scientists being interviewed. Such questions will help establish knowledge, in addition to, determining a data scientist’s ability to elaborate on complicated subjects. Other questions should also be structured to put emphasis on the art and science associated with data science. Examples of such questions can be simple but technical such as why is a comma a bad record separator or delimiter among many more others.
Even though technical skills are crucial in data science; they will need to be applied so that they can solve pending organizational problems. Practical questions, on the other hand, will help establish whether a given data scientist is able to describe any project they have worked on previously and results got from such projects. These questions should also be able to express what aspects of a data scientist technical training have been paying off or important over time in their undertakings. Also, they should also be able to show how a data scientist can apply these skills to an organization he or she is being interviewed for. Such questions may include something like asking a data scientist to describe the recent utilization of logistic regression among others.
Communication based questions
To conclude an interview with a data scientist, an interviewer should establish the communication skills of a data scientist. This is crucial because a data scientist should be able to understand and explain the significance of their results to the problem at hand. Also, these questions are meant to evaluate a data scientist’s ability to communicate both clearly and believably. Such questions may comprise of something like asking a data scientist to explain to the management elites of an organization how they can identify and overcome obstacles in their daily operations and processes.