Evaluation sheet_e4dfa305.xlsx
13.3 KB
Overview:
The Data Science Project Evaluator assesses team submissions in Big Data and Data Science competitions against the project SRS and a 100-mark rubric.
The total number of projects to be checked is 17. The project drive link will be shared with the resource separately.
The role checks that each project actually works, not just that it looks complete: the evaluator re-runs pipelines, verifies metrics against the code, and records fair, evidence-based marks and feedback.
Key responsibilities:
Each evaluation follows the steps, from receiving the submission to recording the final marks. The evaluator needs to check the project for the below parameters given in the table and grade against each parameter as per the maximum marks allocated for each parameter.
Evaluation areas:
The evaluator scores ten criteria that add up to 100 marks.
The evaluation sheet with the parameters is attached.
Required skills:
The evaluator needs hands-on technical depth plus the judgement to score fairly.
Professional:
Qualifications and experience:
Deliverables and quality standards:
For each team, the evaluator delivers:
