Selection Criteria

Candidate Profile

Data Science Experience: Fellow(s) with substantial experience in data science and data technology projects will receive priority. A strong commitment to engaging in social impact initiatives, particularly those involving the use of data science/tech for social good, will be preferred.
Social Sector Understanding: Priority will be given to Fellows who demonstrate a deep understanding of the workings of the social sector. This may include full-time/part-time/volunteer experiences in the social purpose sphere.

Scale of Impact: DOS with the potential to benefit a large number of stakeholders meaningfully will be preferred.
Thoroughness: Proposals that provide a comprehensive explanation of the solution, its features, and benefits for the social sector will be given priority.
Methodological Rigour: Preference will be given to proposals that demonstrate a logical and coherent methodology, along with a realistic approach for undertaking the project.

After an initial round of application reviews, candidates will be shortlisted for interviews. The Panel of Reviewers will select five projects.