Sr. Machine Learning Engineer at Netflix, Inc
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The George Washington University
Master's degree, Computer Science
January 1, 2015 – January 1, 2017
Netflix
Sr. Machine Learning Engineer
February 1, 2022 – Present
Los Gatos, California, United States
Brain Technologies, Inc.
Machine Learning Engineer
May 1, 2019 – December 1, 2021
San Mateo
Crane AI
Machine Learning Engineer Intern
May 1, 2017 – June 1, 2017
Crane AI
Machine Learning Engineer
May 1, 2017 – April 1, 2019
Machine Learning Society
Volunteer in Machine Learning Society
May 1, 2017 – September 1, 2019
Greater New York City Area
NYC Data Science Academy
Data Scientist Fellow
January 1, 2017 – March 1, 2017
500 8 Ave, New York
OIGETIT.com
Machine Learning Engineer Intern
February 1, 2015 – December 1, 2015
718 7th Street N.W., 2nd Floor Washington, D.C. 20001
Diyou
Software Engineer
January 1, 2014 – December 1, 2014
厦门市观音山国际商务营运中心7号楼10楼
MockDown
March 1, 2019 – Present
Create low fidelity mockdowns, redact user information, use for explainer videos or concept walkthroughs.
NBA Player Strength Visualization
June 1, 2018 – Present
A dashboard to visualize individual player's shot data, including a shot chart and 4 line/bar chart. Implemented linked highlighting among all charts using raised common React state among charts. Created a field goal percentage filter to provide more detailed visualization areas with made shots. Developed a match filter to more specifically visualize stats for home, away, won and lost matches.
Kaggle Project
March 1, 2017 – Present
Developed machine learning model with over 1,000 features to predict consumer interest in apartment listings using Logistic Regression, Random Forest, and XGboot
Ink Scrapers
March 1, 2017 – Present
Delivered machine vision classifier for 200K scraped paintings using machine learning algorithms Neural Networks, KNN, PCA, Cluster to predict the author of the painting, discover the similar style of painters
NLP Movie Reviews Analysis
February 1, 2017 – Present
Used Natural Language Processing with Sentiment Analysis to validate numerical movie reviews from Rotten Tomatoes (Used TF-IDF, LDA Topic Modeling, Scrapy)
R Shiny
January 1, 2017 – Present
Built a data product using R shiny and Yelp data to enable exploration of feature importance on small business ratings
Network Analysis Using Enron Email
September 1, 2015 – Present
• Applied various network analytic techniques to explore structural properties in Enron • Constructed a network gragh of communication between Enron employees and identified key players
Generative AI Leader Certification
June 24, 2026 – Present
Google Cloud AI Agents
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards Machine Learning Engineering and AI development, with significant experience at prominent tech companies like Netflix. While there's a strong foundation in data science and analytics, the target role of 'Data Analyst' might be a step down in terms of direct ML model development responsibilities. The projects demonstrate a strong interest in data exploration and visualization, which aligns with a Data Analyst role. However, the primary focus on building and deploying complex AI systems might indicate a preference for more advanced ML engineering tasks. The breadth of skills is good, but the depth is primarily in ML/AI, which may or may not perfectly align with the specific day-to-day tasks of a Data Analyst role, depending on the organization's definition.
Soft Skills & Operational Fit
The candidate's experience at Netflix and Brain Technologies suggests an ability to work in fast-paced, innovative environments. The project descriptions indicate a problem-solving mindset and an ability to translate complex data into actionable insights. The volunteer experience in the Machine Learning Society also points to a collaborative spirit. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.