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Using Data to Drive Private Equity – Lessons, Trends, and Opportunities for Data Scientists

Posted Feb 09, 2022 | Views 5.4K
# Applied AI
# Fireside Chat
Drew Conway
Head of Data Science @ Two Sigma Private Investments

Drew Conway is a prominent data scientist, entrepreneur, author, and advisor to startups, academic institutions, and government agencies. He’s most widely known for his creation of the Data Science Venn Diagram, which was foundational to the field. Drew currently leads data science for Two Sigma Private Investments, where he drives differentiated investment decisions across private equity, venture, real estate and ESG investing. Prior to joining Two Sigma, Drew was the founder and CEO of Alluvium, an enterprise AI company and co-founder of DataKind, a global non-profit of pro bono data scientists.

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Jaclyn Rice Nelson
Co-founder @ Tribe AI

Jaclyn spent the majority of her career at Google partnering with enterprise companies and incubating new products. She was a founding member of the growth team at CapitalG, Alphabet’s growth equity firm, where she advised growth-stage tech companies like Airbnb and Stripe on scaling their technical infrastructure, data security, and leveraging machine learning for growth. In 2019, Jackie and Noah Gale founded Tribe AI to make AI more accessible to companies of all sizes and industries, while also building a new type of career path for top technical talent that emphasizes specialization and freedom. (Read more about it here.) Now, Tribe AI is a highly selective community of 150 machine learning engineers, researchers, and data scientists from industry leaders like Google, Tesla, and Netflix, helping companies solve their toughest business problems using ML.

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Join celebrated data scientist Drew Conway, Head of Data Science for Two Sigma Private Investments and inventor of the Data Science Venn Diagram, in conversation with Jaclyn Rice Nelson, co-founder of Tribe AI, as they discuss the place of data science in the world of private equity.

This talk will cover:

  • An overview of the PE marketplace and trends in how data science gets incorporated into private investing
  • Where data science has been the most valuable when building products
  • Understanding long term and near term forecasting – and the effects of Covid-19 on forecasting models
  • How to programmatically identify comp sets for different asset classes
  • How data science helps you think about price discovery
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