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Data Science for AI Infra @ Meta
AI/ML and Data Science leader with over 20 years of experience. At multiple companies (many with IPO's) grew teams from scratch to 20-50 data scientists who then had massive impact applying data/math/statistics in order to improve the product experience and/or insights that made meaningful business decisions. Instead of specializing in one industry vertical, I leverage my experience in multiple areas (ads, recommender systems, multiple-sided markets, autonomous driving), to bring ideas/concepts from other areas into the current one. An example of this is that at NIO I was the sole inventor in an issued patent which describes a methodology to improve in-car infotainment recommendations by using additional context (e.g. where are you going, who is in the car with you) that a smart-car would have.
Stanford University
MS, Statistics
June 1, 2003 – June 1, 2004
Stanford University
MS, Management Science & Engineering
January 1, 2003 – June 1, 2003
Massachusetts Institute of Technology
SM, Aero/Astro
June 1, 1993 – February 1, 1995
Massachusetts Institute of Technology
SB, Aero/Astro
September 1, 1990 – June 1, 1993
Meta
Director Data Science
May 1, 2025 – Present
Menlo Park, California, United States · Hybrid
Engine
VP Data Science
July 1, 2024 – February 1, 2025
San Francisco Bay Area · Remote
Snowflake
VP, Data Science & Analytics
July 1, 2019 – July 1, 2024
San Francisco Bay Area
NIO
VP, Artificial Intelligence
April 1, 2016 – July 1, 2019
San Francisco Bay Area
Cowboy Ventures
Advisor/Ninja
November 1, 2013 – Present
San Francisco Bay Area
Lyft
VP, Data Science
November 1, 2013 – April 1, 2016
San Francisco Bay Area
Venture Funded Startups
Member, Board of Advisors
April 1, 2011 – Present
San Francisco Bay Area
Netflix
Director, Algorithms & Analytics
July 1, 2008 – November 1, 2013
Los Gatos, CA
Google, Inc.
Statistician
March 1, 2006 – July 1, 2008
Nextag
Statistician
July 1, 2005 – March 1, 2006
Nomis Solutions
Associate, Professional Services
July 1, 2004 – July 1, 2005
Space Systems/Loral
Chairman, Failure Review Board
January 1, 2001 – January 1, 2003
US Navy
Naval Officer
February 1, 1995 – January 1, 2001
Cultural Fit Analysis
The candidate's career trajectory shows a strong fit for high-growth, innovative tech environments, having worked at companies like Google, Netflix, Lyft, and Snowflake. Their experience in building teams and advising startups indicates an entrepreneurial mindset and adaptability. The diverse range of applications (autonomous driving, streaming, ride-sharing, advertising) suggests a broad interest and ability to adapt to different industry challenges, aligning well with dynamic organizational cultures. The target role of 'Data Analyst' seems significantly under-leveled for this candidate's extensive experience and leadership background, which might indicate a potential mismatch in expectations or a strategic career shift not fully explained.
Soft Skills & Operational Fit
The candidate's resume demonstrates strong leadership, strategic thinking, and team-building capabilities, evidenced by their roles in growing and leading data science teams at multiple high-profile companies. Their concept of a 'full stack' data scientist at Snowflake indicates an operational focus on efficiency and minimizing communication overhead. The advisory roles suggest strong communication and influence skills.