
Senior ML Manager at Facebook
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
* Our team works on core ads recommender model improvement, driving big portion of FB company's revenue growth. The team focuses on applied research to push performance boundary of large scale deep learning recommender models. Some of our work include architecture design (e.g., modeling feature interactions), optimization algorithm, graph representation learning, knowledge distillation, sequence modeling and Auction ML. * If you are interested in turning research into impact on one of the largest industry scale recommender systems, please reach out.
University of Minnesota
PhD, Computer Science
January 1, 2011 – January 1, 2016
Zhejiang University
Bachelor, Information Science & Electronic Engineering
January 1, 2007 – January 1, 2011
Senior Manager of Machine Learning
April 1, 2020 – Present
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PhD Intern in eBay Research Lab
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Cultural Fit Analysis
The candidate has worked at top-tier technology companies known for innovation and fast-paced environments (Facebook, Quora, Google, eBay). This suggests an adaptability to high-performance cultures. The transition from Machine Learning Manager to Senior Manager at Facebook indicates career progression and a drive for impact. However, the target role is 'Data Analyst', which is a significant shift from their senior ML management roles. While the candidate possesses strong analytical skills, the alignment with a pure Data Analyst role, which often involves less direct ML model development and more business intelligence/reporting, needs further exploration. The breadth of skills is strong in ML/AI but less explicitly detailed for traditional data analysis tools beyond Hadoop.
Soft Skills & Operational Fit
The candidate's experience as a Senior Manager and Manager indicates leadership, team collaboration, and project management skills. The descriptions suggest a focus on applied research and problem-solving, which are valuable operational fits. However, specific details on communication style or stress handling are not available from the provided data.