
Applied Scientist at Amazon - Machine Learning
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Assessing your cultural and operational fit
Expertise: Machine Learning, Natural Language Processing, Predictive Models, and Deep Neural Network
University of Colorado Boulder
Ph.D, Applied Mathematics
January 1, 2007 – January 1, 2012
University of Houston
MS, Mathematics
January 1, 2004 – January 1, 2007
Shantou University
BS, Mathematics
January 1, 2000 – January 1, 2004
Amazon
Applied Science Manager - Sponsored Brand
June 1, 2025 – Present
Amazon
Senior Applied Scientist - Sponsored Brand
October 1, 2021 – May 1, 2025
Amazon
Applied Scientist
January 1, 2017 – August 1, 2021
Greater Seattle Area
eBay
Applied Researcher-Machine learning
September 1, 2015 – January 1, 2017
Greater Seattle Area
University of Washington
Acting Assistant Professor of Applied Mathematics
August 1, 2012 – August 1, 2015
Greater Seattle Area
Department of Computer Science, University of Colorado at Boulder
Graduate Research Assistant
January 1, 2010 – August 1, 2012
Department of Computer Science, University of Colorado at Boulder
Department of Applied Mathematics, University of Colorado at Boulde
Graduate Teaching Assistant
August 1, 2007 – December 1, 2009
Boulder, Colorado
Department of Mathematics, University of Houston
Graduate Teaching Assistant
September 1, 2004 – July 1, 2007
Houston, Texas Area
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on academic research and applied science within large tech companies (Amazon, eBay). While this demonstrates a rigorous, data-driven approach, the target role of 'Data Analyst' might be a step down in terms of direct research and model development, potentially leading to a mismatch in expectations or underutilization of advanced skills. The breadth of projects is strong in applied mathematics and machine learning, but direct 'Data Analyst' specific projects are not explicitly detailed. The candidate's background is highly specialized in applied science, which may or may not align with the specific cultural needs of a pure data analyst role.
Soft Skills & Operational Fit
The candidate's extensive academic and industry experience, particularly in research and applied science roles, suggests strong analytical thinking, problem-solving, and potentially leadership skills. The teaching assistant roles indicate communication and mentoring abilities. However, specific soft skill assessments are not available.