University of Pennsylvania

Northwestern University

Senior Quantitative Research Analyst at INVESCO

Ariel Investments

Director of Quantitative Research

Self-Initiated Projects with Hugging Face, AWS SageMaker, and Databricks
•	Built sentiment models with Yelp customer reviews and Distilled BERT.
•	Built topic models with Yelp customer reviews using Gensim and SciKit Learn.
•	Processed image data and built classification models with Dogs vs. Cats images and ResNet.
•	Experience with AWS AutoPilot/JumpStart and Databricks AutoML/MLFlow/Spark.

Self Employed

Non Compete Period

Building asset selection, risk, and factor timing models for US Equities using Machine Learning and Alternative data:

“The Promises and Pitfalls of Machine Learning for Predicting Cross-Sectional Stock Returns,” (Co-authored with Harald Lohre, David Mischlich, Yifea Shea, and Maximilian Stroh), Journal of Financial Data Science, Spring 2021. Winner of CFA Germany Investment Research Award 2021.

“Consumer Spending and the Cross Section of Stock Returns,” (Co-Authored with Tarun Gupta, Ph.D. and Viorel Roscovan, Ph.D.), Journal of Portfolio Management, July 2022. Winner of CFA Germany Investment Research Award 2022.

"Machine Learning: Building Factors from Unstructured Data," (Co-authored with Tarun Gupta), Risk & Reward, Q2 Issue, Invesco Quantitative Strategies, 2021.

"Invesco's Guide to Alternative Data," (Co-authored with Tarun Gupta), Risk & Reward, Q4 Issue, Invesco Quantitative Strategies, 2020.

“A Forecast Combination Approach to Equity Factor Timing," (Co-authored with Michael Fraikin, and Harald Lohre, Ph.D.), Risk & Reward, Q1 Issue, Invesco Quantitative Strategies, 2020 (also in SSRN and featured in June 2020 issue of Journal of Quantitative Research, Economics, and Strategy by Wolfe Research).

Presenter at the Neudata Summer Summit on “What is the Promise (or Pitfalls) of Machine Learning for Alternative Data?” June 2021.
Panel discussant on transaction data at the Neudata Winter Summit, December 2020.

INVESCO

Senior Quantitative Research Analyst

•	Conduct initial and on going due diligence on hedge funds for Bear Stearns Fund of Hedge Funds and Hedge Select.
•	Applied quantitative approaches such as k-means clustering and regressions to detect style drift of hedge funds.

Bear Stearns Asset Management

Associate Director

Applied quantitative approaches such as bootstrapping and stratified random sampling to building investable hedge fund indices.

Edward L.