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Making Sense of "Messy" Real Estate Data

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John Maiden
Senior Data Scientist at Cherre
+ 1 speaker
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Reimagining Real Estate
July 28, 2020, New York, USA
Reimagining Real Estate
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John Maiden
Senior Data Scientist at Cherre
Ron Bekkerman
CTO at Cherre

John Maiden is a Senior Data Scientist at Cherre, developing ML/AI solutions to enhance commercial real estate data. His focus is on end-to-end solutions, collaborating with business and technology partners on the initial business concept and working all the way to delivering a product that can face live customers in real-time.John's interest in data science was sparked by an opportunity to work for a technology recruiting startup, writing code and developing models to facilitate effective connections between employers and candidates. Prior to Cherre, he worked at JP Morgan Chase, where his work was delivered to millions of personal consumer customers. He has a BA from Hamilton College and a PhD in Physics from University of Wisconsin - Madison.

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Former Data Science Professor, one of the first five LinkedIn Data Scientists, PhD in Computer Science (Machine Learning), now taming Real Estate data. Extensive experience in commercial software engineering. Expert in Big Data and intelligent Web applications. Well connected both within the industrial and academic Data Mining communities.

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About the talk

Real estate data is inherently noisy, which can make it hard to extract as much value as possible. By standardizing and organizing data to emphasize the relationship between entities, we can discover the complex connections between multiple sources of information that helps customers go beyond their current workflows.


00:15 Intro

01:45 You cannot invest in real estate

02:42 Connecting real estate data sources is easy

04:30 Challenges of name standardization

07:54 Cherre’s knowledge graph

09:10 What goes into a CRE knowledge graph

09:30 Translating this to a knowledge graph (NYC)

11:04 Nationwide knowledge graph

12:42 Building a knowledge graph – lessons learned

16:48 Q&A

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John Maiden
Ron Bekkerman