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Staff MLE | Ex-Microsoft | Ex-Amazonian
I'm a passionate Machine Learning Scientist TL and Manager, with extensive expertise in AI/ML/LLM, Natural Language Processing, GPT prompt engineering, Classification, Recommendation systems, and end-to-end ML system design and deployment. In my most recent role over the past four years at Microsoft, I served as both Tech Lead (2 years) and Manager (2 years) of the Content Services Moderation Science team for our product - Microsoft Start (msn.com). Within Trust Safety and Intelligence, our team utilized AI/ML/LLM and GPT solutions to enhance quality, scalability, and cost efficiency. We achieved 100% automation for proactive approaches, significantly reduced human labeling costs, and delivered high moderation quality to satisfy 2000 publishers worldwide and 100 million DAUs. Prior to joining Microsoft, I spent approximately six years at Amazon, starting as a summer intern. Initially focused on developing fraud detection models for real-time transaction risk mitigation, I later diversified into various impactful projects across different teams. These included contributing to personalized recommendation models for Amazon Payment Products, leading the development of the innovative first-ever smart feature 'Did You Mean?' for home automations, to improve the interaction experience for Smart Home customers through multi-term conversations, and pioneering machine learning applications for Alexa Data services, at Alexa Core AI team.
Stony Brook University
Doctor of Philosophy (PhD), Applied Mathematics & Statistics
January 1, 2012 – January 1, 2015
Purdue University
Master of Science (M.S.), Chemistry
January 1, 2009 – January 1, 2012
Shanghai Jiao Tong University
Bachelor of Engineering - BE
January 1, 2005 – January 1, 2009
Coupang
Staff Machine Learning Engineer
September 1, 2024 – Present
Seattle, Washington, United States · Hybrid
Microsoft
Principal Applied Science Manager
June 1, 2022 – September 1, 2024
Redmond, Washington, United States
Microsoft
Principal Applied Scientist
July 1, 2020 – June 1, 2022
Redmond, Washington, United States
Northeastern University
Adjunct Professor
February 1, 2018 – July 1, 2018
Greater Seattle Area
Amazon
Machine Learning Scientist & Lead
June 1, 2015 – July 1, 2020
Greater Seattle Area
Amazon
Research Scientist Intern
May 1, 2014 – August 1, 2014
Seattle, Washington
Mistakes You Should Avoid at Work
June 24, 2026 – Present
Management Excellence at Microsoft: Model, Coach, Care
June 24, 2026 – Present
Sheryl Sandberg and Adam Grant on Option B: Building Resilience
June 24, 2026 – Present
New Manager Foundations
June 24, 2026 – Present
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Coursera
June 24, 2026 – Present
Writing to Be Heard on LinkedIn
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in Machine Learning and Applied Science, primarily in large tech companies. While this demonstrates a robust technical foundation, the target role is 'Data Analyst'. The candidate's experience is heavily skewed towards advanced ML model development, research, and leadership, which might be an overqualification or a mismatch for a pure data analyst role that typically focuses more on data extraction, transformation, visualization, and reporting rather than ML model building. The breadth of skills is strong within ML/AI, but less explicit in traditional data analysis tools and methodologies. The certifications are primarily soft skills or introductory ML, not directly relevant to core data analysis.
Soft Skills & Operational Fit
The candidate's experience as a Principal Applied Science Manager and Machine Learning Scientist & Lead suggests strong leadership, project ownership, and problem-solving skills. The descriptions indicate an ability to identify issues, recommend scalable solutions, and innovate on algorithms. However, without specific project details or direct assessment, the depth of these soft skills and operational fit for a Data Analyst role cannot be fully determined.