I spent Summer 2022 embedded in The Rockefeller Foundation’s Data Science Team, which is a part of their Innovation Team. One of the team’s focuses for the year was to monitor all the innovative ways the social sector uses artificial intelligence for social good. This work require the team to look at data science techniques and expertise within RF’s grantee network.
As their summer Data Science Associate, I was tasked with building a simple but effective classification model to determine whether or not a grant is data science-related. This model will apply a binary tag -is or is not data science-related — to the foundation’s grants. Knowing which organizations use data-science techniques will help us identify opportunities for future applications of data science. I hope that sharing the process (and code) will be instructive to novice data users looking to adapt this for their own project needs.
For a complete breakdown of the project see my blog post: https://medium.com/mlearning-ai/using-nlp-to-improve-grantee-discovery-adc40f3833f