Data Science Intern

  • Ukraine
  • Full Time

If you care more about what Facebook knows about you — here's the internship of your dreams.

"Knowledge is power," they said. If you know Python (or any other programming language), are familiar with basic statistics, probability theory, and machine learning – then hurry up and apply. We cannot wait to teach you how to turn plain old data into invaluable knowledge.

Here is your test task:

For this test task you need to build a model for predicting real estate prices. You may use any libraries and models (except auto ml and deep learning approaches). Description of fields are in data_description.txt file.

Your aim is to demonstrate skills in data processing and writing of a correct, understandable code. You don’t have to be as precise as possible in your predictions.

Mandatory steps:

  1. Create a Jupyter notebook file to carry out all the further actions.
  2. Open train.csv file as pandas Dataframe.
  3. Choose a metric to evaluate the model and justify your choice
  4. Transform data to the input format of the model
  5. Train the model, evaluate its work
  6. Using the model, make predictions from data with test.csv. Save the result to a prediction.csv file with two columns: Id and SalePrice (check out sample_prediction.csv as an example)

Optional steps:

  1. Conduct basic EDA data. Describe the main features that you should pay attention to
  2. Conduct feature engineering, describe the characteristics obtained and the arguments for their use
  3. Conduct feature selection
  4. Carry out hyperparameter tuning

The result of the test task is a jupyter notebook file.

Attach your completed test task as a file or provide a link to it via the application form below. Look sharp, we won’t process your application if the completed test task is not attached.

Application deadline: May 10

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    Thank you! Your resume has been submitted.

    We will take a look and get back to you if it looks like you’re a fit. Good luck!