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Principal Data Scientist | Observability Engineering
Machine Learning Engineer based in Austin, TX, with over a decade of experience in machine learning and AI. I’ve led impactful projects at industry giants like AWS and forward-thinking health tech companies, tackling everything from recommendation systems and personalization algorithms to predictive modeling. Currently, I’m focused on using AI to discover service disruptions early and improve time to remediation—helping teams respond faster and smarter to incidents through intelligent automation and data-driven insights. My journey from academia to industry has equipped me with a unique lens to bridge theoretical foundations with real-world applications. I’m passionate about mentoring the next generation of data scientists and solving problems that have measurable impact. When I’m not deep in code or data, you’ll find me paddleboarding on Lady Bird Lake or exploring Austin’s trails. Always open to connecting with fellow tech enthusiasts, outdoor adventurers, and anyone curious about the transformative potential of data.
University of Virginia
Doctor of Philosophy (Ph.D.), Computer Science
August 1, 2008 – December 1, 2013
University of Virginia
Master of Engineering - MEng, Computer Science
August 1, 2006 – August 1, 2008
University of Florida
Bachelor of Science (B.S.), Computer Engineering
August 1, 2001 – May 1, 2006
CVS Health
Principal Data Scientist
September 1, 2024 – Present
Austin, Texas, United States · Remote
Amazon Web Services (AWS)
Applied Scientist III
November 1, 2023 – October 1, 2024
Austin, Texas, United States · Remote
BABYLON HEALTHCARE SERVICES LIMITED
Staff Applied Scientist
January 1, 2022 – August 1, 2023
Austin, Texas, United States · Hybrid
Visa
Senior Staff Machine Learning Scientist
June 1, 2021 – January 1, 2022
Austin, Texas Metropolitan Area · Remote
Expedia Group
Senior Machine Learning Engineer
July 1, 2017 – November 1, 2020
Austin, Texas Area · On-site
IBM
Advisory Software Engineer
June 1, 2015 – June 1, 2017
Austin, Texas Metropolitan Area · On-site
The University of Texas at Austin
Assistant Professor
August 1, 2014 – July 1, 2015
Computer Science · On-site
College of William and Mary
Visiting Assistant Professor
August 1, 2013 – July 1, 2014
Williamsburg, VA · On-site
University of Virginia
Graduate Research Assistant
August 1, 2006 – July 1, 2013
Greater Charlottesville Area · On-site
U.S. Naval Research Laboratory
Research Assistant Internship
May 1, 2006 – August 1, 2007
Washington DC-Baltimore Area · On-site
Statistical Learning with Python
edX
June 24, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 24, 2026 – Present
Generative AI with Large Language Models
Coursera
June 24, 2026 – Present
Machine Learning
Stanford Online
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning academia and multiple large tech companies, indicating adaptability to different organizational cultures. Their experience with various domains (healthcare, finance, e-commerce) and technologies suggests a broad interest and ability to integrate into diverse teams. The transition from academic roles to industry, and then through various applied science positions, shows a drive for continuous learning and application of advanced concepts. The target role of 'Data Analyst' seems to be a step down from their 'Principal Data Scientist' and 'Applied Scientist III' roles, which might indicate a mismatch in career trajectory or a specific interest in a more focused analytical role. This could be a point for further discussion to ensure alignment with expectations.
Soft Skills & Operational Fit
The candidate's extensive experience in research and applied science roles suggests strong analytical and problem-solving skills. Their academic background as an instructor implies good communication and mentorship potential. However, without specific project descriptions detailing collaboration or leadership, it's difficult to fully assess operational fit beyond technical contributions.