Creating Your First Data Science Project — Data Scientist Perspective

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1. Solve a Real Business Problem

First, the essential aspect of your data science project is solving a real business problem. It did not matter how great your model metrics were or how fancy the dashboard you developed. If the project did not showcase any possibilities to solve the real business problem, it might not show how you would perform in the data scientist position.

When I talk about real business problems, it isn’t something novel or the most complex problem ever. It could start simple such as:

  • Propensity to buy a new product
  • Prediction of churn customer
  • Fraud detection

And many more. The point is that the business problem stated above are realistic and often shown up in every company. You might think it was evident that you should present a real project. However, you would surprise by how many people, including an absurd project.

Another question is, how could you stand out from all the other applicants if everybody has the same things in mind? To stand out, try to imagine your dream company by answering the following questions:

  1. Where do you want to work?
  2. What kind of industry do you want to employ?
  3. What business problem from the industry and company do you want to solve?
  4. How would you present the solution to the management?

Why do I ask you to imagine the dream company? Because to stand out from the others, the best way is to have a data science project that solves the business problem presented in the company you want to apply.

If you are applying for a data scientist position in the insurance company, the company might notice you if the project is about re-insured prediction. However, the re-insured project might not be suitable for the company with image-detection products. By imagining your dream company, you would have a direction for your first data science project.

In short, try to develop your data science project that solves a business problem and is specific to the company you imagine.

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