As the data field matures, there are increasing opportunities for data scientists to look beyond the typical places where data roles proliferate, like tech startups, financial firms, or health care companies, towards problems with a clear social focus. But, are these areas really all that different? This talk will explore the false distinction between those working in "corporate data science" and those doing "data for good" and describe how all data practitioners can engage with the social challenges built into their work. In particular, we'll focus on the importance of power dynamics, co-creation, and mindful decision-making in navigating the social impacts of data science projects. We'll also highlight some of the unique challenges posed by data scientists working in the social sector and cover some tips for anyone considering making a shift towards the social side of the data spectrum themselves.
Data for Good: What Could Be Better?
As GlobalGiving’s first Data Scientist, Nick wears many hats. Whether leading the organization’s data strategy, building and maintaining production data pipelines and rewards algorithms, or designing experiments to evaluate program impact, Nick lives to make social good data accessible, understandable, and actionable for everyone at GlobalGiving and beyond. He’s also part of the team behind Aidsight, an app allowing non-tech users to easily explore international aid transparency data to unpack hidden relationships between organizations and validate data quality, and the developer of Pando, a platform for exploring networks of changemakers in the social sector. In his past life, Nick worked as a reliability consulting engineer for Fortune 500 companies around the world and held NSF research positions in China and Thailand. Outside the office, he is a folk music street performer, amateur haiku poet, and worm farmer. Find out more about Nick on Twitter (@nicholashamlin) or at globalgiving.org.