Collaborate with Jupyter notebook for data science interviews

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 and more.

Automatically rank candidates

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 relevant data science database questions for the job role

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) to specific language environments like Python, R, or SQL.
  • Conduct your live collaborative interview, or deploy your project as a take-home (asynchronous) project.
Present candidates with realistic interview environment

Give candidates a fully functional, realistic interview environment including:

  • Ample processing power to handle super large data sets.
  • A fully-functional Jupyter Notebook environment.
  • Ability to import and utilize any package or library.
  • Plot data and run individual cells in the notebook.
  • Access to the server, shell and console.
Review data science interview candidates as a team

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