Enabling Purchase of Residential Homes at Scale

Properly buys and sells homes directly from consumers. For our business to be successful, we must be able to predict two things when making a home purchasing decision: ? The price it would sell for on the open market ? How much time it will spend on the market to sell at that price These two variables are correlated: price can affect time-on-market, and time-on-market can affect price. There are many other factors at play as well. In the broader market, these complex real estate decisions are largely made using human judgement, based on experience and expertise. We want to increase the speed and accuracy of these predictions using applied data science, in order to reduce the business risk of home buying decisions, and to allow making them at scale.

Faculty Supervisor:

Nathan Taback


Bharadwaj Janarthanan




Computer science


Real estate and rental and leasing


University of Toronto



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