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How JustGiving turns data into donations

Published Mon 25 Feb 2019

JustGiving is passionate about using data. At the heart of its efforts in data science is its ‘give graph’ containing over half a billion relationships and 96 million nodes, interconnecting users, charities, fundraisers and crowdfunders.

Catch Richard Freeman PhD, lead big data and machine learning engineer at JustGiving at Big Data World 2019, to learn about the tools and processes that underlie machine learning and data science at JustGiving, as well as tips for pitching data science projects to your board.

Register for BDW for free at: www.tkrt.io/2019reg

Richard is a lead big data and machine learning engineer at JustGiving, a tech-for-good company that’s helped 25 million users in 164 countries raise $5 billion for good causes, acquired in 2017 by Blackbaud the world’s leading software company powering social good. He currently leads the delivery and architecture of its in-house data science platform. He is also an independent freelance consultant helping organisations with cloud architecture, serverless computing and machine learning at Starwolf.

Richard has 15+ years’ experience delivering small to very complex projects for clients including Fortune Global 500 companies, in a variety of sectors including nonprofit, insurance, recruitment, financial services, government and e-commerce. He was previously a developer and later solution architect at Capgemini. Richard holds an MEng in computer systems engineering and PhD in machine learning and natural language processing from the University of Manchester, giving him a solid foundation in software engineering and data science.

He is a blogger and speaker presenting at events like AWS Re:Invent and AI Summit, and an author of two serverless video courses by Packt (also available on O’Reilly Safari and Udemy) and working on a serverless related book.

www.tkrt.io

Experts featured in Video:

Richard Freeman, PhD

Lead Data and Machine Learning Engineer
JustGiving

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Tags:

Big Data machine learning natural language processing
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