Research quantitative strategies for improving team performance

IID is an angel collective composed of 30+ leading data executives investing in and advising promising data startups.

Led quantitative strategy for the Minnesota Timberwolves, focusing on improving team decision quality with models and analysis. Managed all engineering, data science and analytics functions.

Led the Data Science and Analytics teams at Motive. We tackled some of the biggest problems in transportation using cutting-edge machine learning and statistical models. Example projects:* Geospatial modeling problems using high dimensional sensor data from our network of hundreds of thousands of connected trucks* Predictive maintenance and outlier detection* Edge deployment of realtime machine learning algorithms

Conducted research on model predictive control using deep neural networks to do action-conditional video prediction

Led finance optimization team, using mathematical optimization to drive high leverage decision-making.

Built predictive models to aid in player evaluation for the "Process Era" 76ers

Conducted original research in dynamic realtime online allocation for online ad exchanges

Developed models of market expectations using futures, options, caps and other interest-rate and inflation derivatives.

Assisted economists in the research and execution of quantitative models of financial assets

Back-end software engineer building systems using Java Spring and Hibernate.