Two people on a video call during a Jupyter notebook

The most effective and realistic way to interview for data roles.

Create and customize interesting and challenging questions for candidates to solve in Jupyter Notebook, Python, R, SQL, spreadsheets and more.

Automatically rank data science candidates with easy-to-set-up assessments

  • Test for proficiency in data science principles, data analysis, SQL, Python, and R.
  • Use multiple-choice and free-form questions, programming exercises and gamified challenges.
  • Pick the best candidates to go forward with, based on their skills.

Design and customize the interview questions so they’re relevant to the role

  • Establish a PostgreSQL or MySQL database with relevant data for the candidate to query.
  • Generate a dataset in any format, such as JSON, CSV or Parquet or any other preferred data type.
  • Configure a specific environment for your interview ranging from Jupyter Notebook (SciPy, Minimal, R, TensorFlow) or Google Sheets to specific language environments like Python, R, or SQL.
  • Conduct your live collaborative interview, or deploy your project as a take-home (asynchronous) project.

Give candidates a fully functional, realistic interview environment

  • Ample processing power to handle super large data sets.
  • Fully-functional Jupyter Notebook environment.
  • Import and utilize any library or package .
  • Plot data and run individual cells in the notebook.
  • Access the shell, server and console.
  • Collaborate with candidates in a fully-functional instance of Google Sheets.

Collaboratively review candidates as a team and build a world-class organization

  • Private interview notes capture the hiring team’s feedback.
  • Save the candidate’s final output for objective review.
  • Confidently make your next data science hire(s).

Jupyter Notebook Online Sandbox

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