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Senior MLE@Siri LLM
• Solid background in Natural Language Understanding, Machine Learning, statistical modeling, A/B testing, data structure and algorithms, data visualization, etc. • Hands-on experiences on leveraging analytics and large amounts of data to drive significant business impact. • Proficient with programming in Python, R, SQL, SAS, WinBUGS, MATLAB, Tableau. • Impactful presentation skills, including the use of meaningful charts, graphs, or other data visualizations to convey information and results clearly and concisely. • Passionate about data science and enjoy working in a collaborative environment. You can reach me by cp2xd@virginia.edu.
University of Virginia
Doctor of Philosophy (Ph.D.), Statistics
January 1, 2011 – January 1, 2016
University of Virginia
Master of Science (MS), Statistics
January 1, 2011 – January 1, 2012
Shanghai University of Finance and Economics
Bachelor of Science (BS) & Bachelor of Management, Statistics & Accounting
January 1, 2007 – January 1, 2011
Apple
Senior Machine Learning Engineer @ Siri Understanding
September 1, 2019 – Present
San Francisco Bay Area
Amazon
Research Scientist II at Alexa AI
July 1, 2017 – June 1, 2019
Sunnyvale
Genentech
Data Scientist
August 1, 2016 – June 1, 2017
South San Francisco
Novartis Oncology
Data Scientist
January 1, 2016 – August 1, 2016
Bristol-Myers Squibb
Data Scientist Intern
June 1, 2015 – December 1, 2015
Princeton, New Jersey
FDA
Statistician Intern
June 1, 2014 – August 1, 2014
Silver Spring, MD
Statistical Bioinformatics Group, University of Virginia
Part-time Statistician
January 1, 2014 – June 1, 2015
Charlottesville, Virginia Area
Cultural Fit Analysis
The candidate has a strong background in research and development within large, innovative tech and pharmaceutical companies, which suggests a fit for data-driven, fast-paced environments. The transition from research scientist/ML engineer to a Data Analyst target role might indicate a desire for more direct business impact or a shift in focus, but the core analytical skills are highly relevant. The breadth of experience across different industries (tech, pharma, government) demonstrates versatility.
Soft Skills & Operational Fit
The candidate's experience descriptions indicate collaboration with product and engineering teams, mentoring junior scientists, and presenting findings, suggesting good communication and teamwork skills. The diverse project experience implies adaptability and problem-solving capabilities.