Proximilar is an NYC-based startup that builds forecasting algorithms by combining the tools of AI with fundamental analysis. Most of today’s equity research still relies on 20th century valuation models. That leaves room for dramatic innovation.
Bring evidence-based AI methods into mainstream investing. Lay the foundation for a more honest and rational world of finance.
Dmitriy spent a decade modeling and marketing equity derivatives for corporate clients at UBS, working at the juncture of quantitative and corporate finance. More recently he has been developing trading algorithms and became fascinated by applications of machine learning in finance, particularly its potential to radically improve the forecasting of corporate performance. He holds an MBA from Columbia. His undergraduate degree is in Applied Mathematics.
Olga has more than 20 years of technical experience and expertise in the financial industry. Prior to co-founding Proximilar, Olga held various technology roles at Merrill Lynch, Lehman Brothers, Barclays, and Deutsche Bank, focusing on building software systems for Market Risk and Equity Trading technology. She holds a MS in Computer Science from Columbia University and BS in Mathematics and Computer Science from Brandeis University.