Data Science Test Reports

You can view the Test report of a candidate after the candidate has taken a test.

For Data Science project type Questions, the report displays the Candidate's performance score based on the evaluation criteria if the question has the script configured to score and evaluate the performance of the submission. 

In absence of an automatic scoring setup, the report displays the Candidate's performance score based on manual scoring by the Hiring Manager.

To understand how a Data Science Question is scored, read our article: Scoring a Data Science Question.

A Data Science Test Report provides a complete analysis of a particular candidate's test attempt, time, solution, and candidate details. 

Prerequisites

• You must be logged in to your Hackerrank for Work account.
• The candidate must have attempted the test and a report must have been generated.

Steps

1. Click the Tests tab and then click the required test name from the displayed list.
2. Click on the Candidates option on the pane below the test name, and then click the required button from the left-hand pane that shows various candidate status options. 
3. Click on the candidate name to view the report for the required candidate
4. You can view the Summary and Timeline tabs. Click each tab to view different details.
5. The Summary tab provides an overview of the candidate, an option to generate an interview invite, and displays the overall score. You can also scroll down to check the 'Skill score’ mapped to the skills in the respective test, leave comments, and more.
6. Click on the View Report beside your desired question from the Questions section to view a detailed analysis of the candidate's solution, with options to review and evaluate the candidate's Jupyter Notebook.
7. The Report provides two options to evaluate the Candidate's solution in the submitted project files—download Zip and Review in Jupyter. 
8. Click Evaluate to automatically open the Candidate's project and review the submitted solution. You can change the candidate's notebook, run scripts, and figure out precisely the candidate's approach to solving the question, whether they have addressed various corner cases, and so on. This approach does not require downloading the project locally. Learn more about Review in Jupyter by reading our article on Scoring a Data Science Question.
9. The Timeline tab in a Data Science Question shows the series of events when the candidate solved the question.

What's Next?

• After reviewing the report, you can click the Candidate Status button to change the candidate's status to one of the available options depending on whether the Candidate's performance qualifies for further steps in the hiring process. For example: If the Candidate's Test performance proves satisfactory, you can set the status to "Passed".