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Data Science Technical Case

About the Case.

... It's not just a Kaggle competition!

To evaluate the technical skills of our Data Science candidates, we kindly ask you to solve the challenge in the link below. This is a demand forecasting problem where you must build a model able to forecast weekly sales for different departments, stores, and retailers.

Here are some instructions (and tips!) for your solution:

  • Your resolution must be developed and delivered on a Kaggle notebook;
  • Please, build your solution in an organized and structured way, because we want to understand what steps you took to develop your model;
  • We also expect to read a text containing your solution justifying the decisions made and highlighting the main conclusions (example: why you decided to plot a graph, explain what conclusions you can extract from it; or why you are choosing a particular model, make it clear which was the criterion for choice). It's super important that our team can follow your way of thinking without following the lines of code!
  • Code quality is also very important, so keep in mind that well-written code warms our hearts!
  • Super tip: a clear and well-structured rationale is more important than a model with very high performance! Also, we often need to explain our reasoning to a non-technical audience, so it's worth exercising your ability to explain complex concepts simply!

About delivering the Case

Once you finish the challenge, please follow the instructions on this form.

Important!

  • Remember to make your Kaggle notebook public so we can access it;
  • Be aware to present your solution if called for a technical interview!

Good luck and have fun,

Ze´s Data Science Team