Drew Conway is a prominent data scientist, entrepreneur, author, and speaker. He's built companies and has advised and consulted on the applications of data science and engineering across many industries. Ranging from fledgling startups to Fortune 100 companies, as well as academic institutions and government agencies. Drew joined Two Sigma in 2019, and is a Managing Director and Head of Data Science for Two Sigma Private Investments Group. He leads the research and development of tools designed to directly support the investment process across all of Two Sigma's private investment businesses, including venture capital, private equity, and real estate. He is well known for the development of the Data Science Venn Diagram, which outlines how data scientists fit into the data analytics ecosystem. Drew is also the author of "Machine Learning for Hackers," a popular introductory text on machine learning techniques. Drew is recognized for his work in the NYC technology community, where he co-founded DataKind (2011), a global non-profit network of pro bono data scientists. Drew is a former senior advisor to the Mayor's Office of Data Analytics for the City of New York, and he previously served as an advisor to Mortar Data (acquired by Datadog in 2015) and YHat (acquired by Alteryx in 2017). In 2015, Drew founded Alluvium to bridge the gap between industrial machine data and the business and consumer users who use this data to make better decisions. He served as CEO and was the driving force behind the company's vision and growth, until its acquisition in 2019. Drew was awarded the MacCracken Fellowship and earned a PhD in Politics from New York University in 2013. He also earned a BA in Computer Science from Hamilton College in 2004. Drew started his career as a computational social scientist in the U.S. intelligence community, supporting the U.S. counter-terrorism mission.
Tue Apr 09 2:30 PM — 3:30 PM (GMT-05:00) Eastern Time New York Hilton Midtown - Level 2, Sutton South
Commercial real estate used to be a fairly staid sector, but exogenous shocks to the system such as global pandemics, macroeconomic shifts, and climate change have created a need for faster, more nimble decision-making to increase returns and mitigate risks. Leveraging the vast quantities of data available through the use of machine learning and artificial intelligence can create tools to explain the current state and predict likeliest future states, but acquiring data and the ability to use it effectively costs money and time. After a brief introduction to the topic, the panelists will talk about how their companies have deployed data science and artificial intelligence to create a competitive advantage.