Chuong (Tom) Do Email & Phone Number

San Francisco, CA, US

• I lead the data organization, a 90+ person group of data scientists and engineers covering:
• product analytics: influencing decision-making through opportunity sizing, metrics/dashboard design, ad hoc and strategic analyses, and experimentation design/analysis/interpretation.
• analytics engineering: delivering standard analytics-ready, high-quality data assets (i.e., tables, data dictionaries) for core data and process domains.
• data products: developing production-ready machine learning and deep learning-based systems that directly power customer experiences and drive internal efficiency.
• data governance: establishing the processes and policies used to ensure the availability, usability, integrity, and security of data.
• data platforms: providing the fundamental systems and infrastructure used by all data applications, such as data warehousing, data operations, resource provisioning, and workflow management.

Mountain View, CA, US

• Built and led Coursera's end-to-end data organization from scratch to ~30 in size. Had the privilege to work with an amazing cross-disciplinary group of software engineers and data scientists spanning:
• decision science (metrics, reporting, experiment design, statistical analysis, forecasting)
• data products (modeling, algorithms, machine learning, search/recommendations, "next generation" technologies)
• business intelligence (data governance, curation, standardization)
• data infrastructure (data warehousing, data access and visualization, A/B experimentation, surveys/instrumentation, machine learning infrastructure, personalization, research, email infrastructure, data science.
• Independently built data function from the ground up

Sunnyvale, California, US

• Developed core machine learning algorithms underlying the Ancestry Composition feature, including:
• a haplotype graph-based method for large-scale computational out-of-sample phasing using extremely large reference panels (over 100,000 individuals)
• a multi-class support vector classifier for ancestral classification of haplotype segments
• a dynamic Bayesian network model for simultaneous local ancestry deconvolution and phasing error correction
• a regularized isotonic regression-based procedure for recalibration of classification reliability estimatesDeveloped a highly parallelized and scalable architecture for large-scale statistical genetic analysis.
• a volume-based abstraction for efficient storage and manipulation of dense imputed genotype data

Doctor Of Philosophy (Ph.D.), Computer Science

Master'S Degree, Computer Science

Bachelor'S Degree, Mathematics

Bachelor'S Degree, Biological Sciences

High School