/ds-intern-test

Technical exercise — Data scientist intern @ Giskard

Primary LanguageJupyter Notebook

Technical exercise - Data scientist intern @ Giskard

Hi! As part of our recruitment process, we’d like you to complete the following technical test in 10 days. Once you finish the exercise, you can send your notebook or share your code repository by email (matteo@giskard.ai). If you want to share a private GitHub repository, make sure you give read access to mattbit.

If you have problems running the notebook, get in touch with Matteo at matteo@giskard.ai.

We hope this assignment will also offer a chance to learn something new. Good luck!

Overview

We have two available internship tracks:

  • Data scientist (Research & Development)
  • Data scientist (Technical Writing)

Based on the track you decided to follow, you will need to complete a different assignment. If you are interested in both tracks, you can complete both assignments.

Data scientist (Research & Development)

The assignment for Data Scientist Intern in the Research & Development team is presented in this notebook: DS_R&D_Assignment.ipynb. The assignment consists in 5 exercises, in increasing order of difficulty. The first three exercises should be relatively simple, you shouldn’t spend too much time on them.

All the files needed in the exercises are included in this repository (e.g. points_1.npy, stopwords.txt).

Keep in mind that we strongly value:

  • code quality, clarity & neatness
  • short and straight to the point explanations if needed
  • reasoned processes more than brute-force solutions
  • reasoning more than the outcome

Data scientist (Technical Writing)

You will find the assignment for Data Scientist Intern for Technical Writing in this notebook: DS_TechWriting_Assignment.ipynb. The assignment consists in 2 exercises, the first one is a technical exercise and second a writing one.

All the files needed in the exercises are included in this repository (e.g. stopwords.txt).

Keep in mind that we strongly value:

  • code quality, clarity & neatness
  • short and straight to the point explanations if needed
  • reasoned processes more than brute-force solutions
  • reasoning more than the outcome