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My passion has always been about finding the signal in the noise and, more generally, finding patterns in numbers. Whether it's finding submarines in a noisy ocean, fraud in a stream of transactions, or the design that minimizes wasted time or effort, I'm at home in data. I first lived this passion as an electrical engineer, focused on digital signal processing for defense and intelligence applications. In the last decade and a half, I've been a practicing data scientist and model risk officer, where I've focused on the application of various machine learning (ML) algorithms to business problems at Capital One. A second passion that has emerged is sharing what I've learned with others through teaching and mentoring. I was a founding member of Capital One's Tech College, leading the machine learning discipline. Since it's founding, my team and I have conducted in-person machine learning training for over 4000 enrollees and several thousand more who have taken advantage of our self-paced training. I'm known for blending hands-on work and leadership. I don't like to get too far away from the technical details, but also like having a say in strategic choices and direction. So far, I've been successful at navigating that edge between manager and technologist. If you noticed the picture at the top of the page, bicycling is one of my favorite activities. I've been riding in Bike MS since 2002, and am approaching $50,000 raised for the National MS Society. My wife and I also like to hike and discover new places to visit. Expertise: Machine Learning, Data Science, Training, Team Leadership, Model Risk Management, Python, Linux/Unix, Fraud Detection, Credit Risk, Marketing Response, Data Mining
University of Virginia
Doctor of Philosophy (PhD), Systems Engineering, Operations Research
N/A – Present
The University of Texas at Austin
Bachelor's of Science (BS), Master's of Science (MS), Electrical Engineering
N/A – Present
EnergyHub
Principal Machine Learning Scientist
June 1, 2022 – Present
Brooklyn, New York, United States
Capital One
Distinguished Machine Learning Engineer (Director): Center for Machine Learning
April 1, 2020 – July 1, 2022
Capital One
Director, Data Science: Dean of Machine Learning and AI, Capital One Tech College
January 1, 2016 – April 1, 2020
Capital One
Director. Data Science: Divisional Model Risk Officer
January 1, 2013 – January 1, 2016
Capital One
Director. Data Science: Small Business Banking
January 1, 2011 – January 1, 2013
Capital One
Director of Data Management
January 1, 2009 – January 1, 2011
Capital One
Sr Manager of Statistical Analysis
January 1, 2006 – January 1, 2009
Capital One
Director of Data Management
January 1, 2003 – January 1, 2006
Capital One
Software Developer / Architect
January 1, 1997 – January 1, 2003
DXC Technology
Advanced Systems Engineer
July 1, 1994 – July 1, 1997
Raytheon
Systems Engineer
December 1, 1989 – July 1, 1994
Cultural Fit Analysis
The candidate has a very strong background in large enterprise environments, particularly in financial services. Their experience in leading educational initiatives (Capital One Tech College) and managing model risk demonstrates a commitment to best practices, governance, and knowledge sharing. While the experience is deep within specific domains, the breadth of roles from software developer to principal ML scientist suggests adaptability. However, the target role of 'Data Analyst' might be a significant down-leveling from their 'Principal Machine Learning Scientist' and 'Distinguished Machine Learning Engineer' roles, which could pose a cultural fit challenge regarding role expectations and growth opportunities.
Soft Skills & Operational Fit
The candidate's extensive leadership experience in establishing technical colleges and managing model risk suggests strong communication, strategic thinking, and operational leadership skills. Their long tenure at Capital One indicates loyalty and ability to navigate complex organizational structures. The descriptions highlight a focus on value-add activities beyond mere compliance, indicating a proactive and results-oriented approach.