
Machine Learning Lead
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Maryland
PhD, Applied Mathematics & Statistics & Scientific Computing
January 1, 2014 – Present
Nanjing University
B.S., Mathematics
N/A – Present
Stealth Startup
Co-Founder
May 1, 2026 – Present
Grow Therapy
Machine Learning Lead
January 1, 2026 – January 1, 2026
Snap Inc.
Machine Learning Engineer
January 1, 2023 – January 1, 2026
DoorDash
Software Engineer, Machine Learning
January 1, 2022 – January 1, 2023
San Francisco Bay Area
DoorDash
Staff Machine Learning Applied Scientist, TL
January 1, 2020 – January 1, 2022
San Francisco Bay Area
Airbnb
Data Scientist, Tech Lead
December 1, 2019 – June 1, 2020
Airbnb
Data Scientist, Algorithms / Machine Learning, Tech Lead
February 1, 2019 – December 1, 2019
Adobe
Manager, Tech Lead, AI/ML applications
May 1, 2016 – February 1, 2019
Adobe
Data Scientist, Machine Learning
September 1, 2014 – May 1, 2016
Liberty Mutual Insurance
Statistician Intern -- Predictive Modeling
June 1, 2013 – August 1, 2013
Greater Boston
Cultural Fit Analysis
The candidate has a diverse background working at various tech giants and a startup, indicating adaptability to different organizational cultures. Their experience spans multiple domains within ML/Data Science (e.g., ads, recommendations, NLP, marketing), suggesting a broad interest and ability to contribute to different business challenges. However, the target role is 'Data Analyst', which is a significant shift from their extensive senior/lead Machine Learning and Applied Scientist roles. While they possess strong analytical skills, the role alignment is not direct, potentially indicating a mismatch in career trajectory or expectations for a pure Data Analyst role.
Soft Skills & Operational Fit
The candidate's resume indicates strong leadership and team management skills through roles like 'Machine Learning Lead', 'Staff Machine Learning Applied Scientist, TL', 'Data Scientist, Tech Lead', and 'Manager, Tech Lead'. The descriptions highlight initiating new areas, leading teams, and driving significant business impact, suggesting strong operational fit and ability to work autonomously and collaboratively. However, without specific psychometric or communication test results, a definitive assessment of soft skills like stress handling or team collaboration is limited.