Currently, the field of data science is tipped towards big players that are able to invest in compute resources and acquire the best talent, whether in corporate giants in Silicon Valley or big government actors. Smaller players like community groups, charities, cooperatives, and academics, are increasingly priced out. Even larger social impact organizations (SIOs) or academic institutions face an uphill battle to compete for the engineers, designers, and data scientists needed to deploy data science effectively and at scale.
This resource examines the complexity of data science for the social impact field and how building an interdisciplinary team is essential for the growth of an organization.
Related Guides & Resources
This guide is for organizations looking to build their data science for social impact teams. Resources include hiring best practices, job description templates, websites, and sample applications for social impact organizations to share their open positions.
Resources from NTEN, Massachusetts Institute of Technology (MIT) and +5