FIP 015: Pro-bono Data science with Jake Porway

In this episode, Jake Porway talks us through DataKind, the organization he founded that helps connect data scientists with non-profits. He was previously with the New York Times as a data scientist so is a great person to have on the show to unpack how data can help non-profits make better decisions on the allocation of resources.

Some of the things you’ll learn on this podcast include:

  • A quick overview of data science and how big data, statistical modelling, machine learning, and artificial intelligence all fit together.
  • How DataKind brings together data scientists with social organizations to work on projects together, and how they facilitate developing the scope of the project, the design and the process of working together.
  • How to start right, which means coming up with the question to answer, rather than the data to use.
  • How the Red Cross worked with data scientists to to predict where fires were more likely to happen across a city.
  • How the Gates Foundation worked with data scientists and satellite imagery to help prevent the spread of wheat crop disease affecting subsistence farmers.
  • How more and more Corporates are sharing their data of human interactions to help with social problems, like a financial transactions of refugees or social media activity.
  • The six components that DataKind brings together for a successful project: a smart problem statement, data sets, data scientists, funders, subject matter experts, and the social actor who will use it at the end of the day.
  • How a crisis textline organization connecting teens in crisis with councilors, used data science to predict which texts were the most urgent, so resources could be allocated more effectively and lives saved.
  • How 14,000 data scientists are standing by with DataKind to help tackle social problems around the world and how you can take advantage of this incredible resource.


Connect with Jake

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.