Converting Business Problems to Data Science Problems
In a lot of Data Science interviews, it is common to ask business related questions. The interviewee is expected to solve the challenge faced by a business in an interview. For example, the profits earned by a newspaper company is dropping, what can be done to rescue the situation. How Reliance Jio can decide if it is beneficial to start its operations from a new location. How the launch of Baba Ramdev SIM will affect the business of Reliance Jio, etc.
It is common for Interviewees to prepare well for Data Science questions. They expect and prepare well for questions like, “How to impute missing values”, “How do you decide which algorithm is suitable for a dataset”. However, the candidates are completely baffled when they face business cases. A part of the reason is that the candidates are not expecting business case questions in an interview. Another reason being none of the data science blogs or courses does not touch upon how to convert business problems to data science problems. There are frameworks available for Data analysis but they are surprisingly quiet on how to convert the business to data problem. For example, the CRISP-DM framework is very famous for Data analysis. The first and second steps of CRISP-DM are ‘Business understanding’ and ‘Data Understanding’. Most of the aspiring data scientist does not know how to proceed from the 1st to 2nd step. The aim of this article is to fill this gap. Victor Cheng’s book and videos helped me in understanding how to convert business problems to data problems. This article is based on his teachings.
Interviewer’s Mindset
Before diving-in how to answer case interviews, let us understand the interviewer’s mindset. What are the interviewers looking for when they ask business questions? Some of the things which interviewers are looking for are:-
- Do the candidates possess independent thinking mindset?
- Are the answers good enough if not precise?
- Are the solutions offered by the candidate client friendly (In case of consulting companies)
- Is the solution offered by the candidates linear?
- Did the candidate explain the solution visually?
- Is the candidate’s solution practical to implement?
The candidate solution should proceed linearly and logically from a challenge to a solution. If the solution is scattered, jumping from one point to another arbitrarily then that interview is over immediately in the mind of the interviewer. Additionally, a right approach with a wrong answer is preferred over a right answer with a wrong approach. If the approach is wrong and the answer is correct, interviewers will assume that the candidate got lucky. This will not be the case in all situations. If the approach is correct then it is repeatable and can be applied to many business situations.
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