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Uniting Data Science and Social Good, with DataKind co-founder Jake Porway

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Treść dostarczona przez Jim Fruchterman. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Jim Fruchterman lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

"What could the nonprofit sector do if every nonprofit had Google's engineering team?" (J. P.)

In this thought-provoking episode, we sat down with Jake Porway, the visionary co-founder of DataKind, to explore the transformative potential of harnessing data science for the nonprofit sector. Jake takes us through the journey of the organization from its early days of hackathons to its evolution into a beacon for long-term, impact-oriented projects.

Today, DataKind is made of many chapters worldwide, as data scientists and social workers meet to face challenges in their home countries. But we asked Jake about high-level issues as well — aspects he has put much thought into: Do nonprofits need their own data science teams? If not, what is the right model to leverage data science skills when the alternative is an incredibly high-paying job in the for-profit sector? Are organizations like DataKind suitable for generating products that scale or does their true value lie in creating a platform for much needed (and underfunded) Research and Development in the service of social impact?

This episode is a must-listen for anyone who is working in tech, and is looking for a way to put their skills towards something more than ad campaign optimization.

> Transcript on website

RATE, WRITE, SUBSCRIBE

Be sure to leave us a rating on Spotify or a review on Apple Podcasts!

Wicked problems require more than one line of thought — was there anything you agreed or disagreed with? Anything you'd like us to explore further? Write us a note at podcast@techmatters.org and follow us on LinkedIn!

  continue reading

18 odcinków

Artwork
iconUdostępnij
 
Manage episode 408350636 series 3563026
Treść dostarczona przez Jim Fruchterman. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Jim Fruchterman lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

"What could the nonprofit sector do if every nonprofit had Google's engineering team?" (J. P.)

In this thought-provoking episode, we sat down with Jake Porway, the visionary co-founder of DataKind, to explore the transformative potential of harnessing data science for the nonprofit sector. Jake takes us through the journey of the organization from its early days of hackathons to its evolution into a beacon for long-term, impact-oriented projects.

Today, DataKind is made of many chapters worldwide, as data scientists and social workers meet to face challenges in their home countries. But we asked Jake about high-level issues as well — aspects he has put much thought into: Do nonprofits need their own data science teams? If not, what is the right model to leverage data science skills when the alternative is an incredibly high-paying job in the for-profit sector? Are organizations like DataKind suitable for generating products that scale or does their true value lie in creating a platform for much needed (and underfunded) Research and Development in the service of social impact?

This episode is a must-listen for anyone who is working in tech, and is looking for a way to put their skills towards something more than ad campaign optimization.

> Transcript on website

RATE, WRITE, SUBSCRIBE

Be sure to leave us a rating on Spotify or a review on Apple Podcasts!

Wicked problems require more than one line of thought — was there anything you agreed or disagreed with? Anything you'd like us to explore further? Write us a note at podcast@techmatters.org and follow us on LinkedIn!

  continue reading

18 odcinków

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