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Data Science Interview Handbook

Data Science Process Pipeline

Explore the entire data science process pipeline, including problem identification, data collection, cleaning, exploration, modeling, and communication. This lesson helps you understand how to break down projects and clearly explain your approach during interviews, ensuring you showcase your data science skills effectively.

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Performing data science is a process, and every part is crucial. To explain any of your projects during an interview, divide them into these processes. That will give the interviewer an understanding of both your problem and your solution.

Identify the problem

Today, a lot of people and companies want to implement data science and machine learning into their businesses, but they don’t know the exact power and capability of the field. Data science has some limitations, and it is important to understand these limitations before diving in.

We need to start by identifying the right problem. In order to do this, we first need to understand the business.

For example, if we want to do something like recommend a marketing campaign, we first start by asking questions such as:

  • Who are the customers?
  • What products are associated with this campaign?
  • What is the measure of a successful campaign?
  • What are the expectations (in terms of profit or business value) of this campaign?
  • What is the risk? If we do not succeed in the campaign, what is the loss?
  • What is the existing approach and what were the benefits in the past?

    With these kinds of problems, we may discover that the company wants to increase its revenue ...