Sean Chao Email & Phone Number

Cupertino, California, US

• Lead a data science team focusing on evaluating and improving AI/machine learning features in Apple services
• Human-in-the-loop model development
• LLM evaluation and alignment
• AI safety
• Quality control of annotation data

Cupertino, California, US

Experimentation, offline evaluation for Apple services (App Store, Apple Music, Apple TV, Apple Books, Apple Podcasts)

San Francisco, CA, US

• Trust Tools and Operations
• Built an automated business report with 10+ key operational metrics to serve as the source of truth in providing data rigor and clarity for senior leaders
• Served as the primary data partner for Trust tools product to build, monitor, and improve internal agent tools
• Defined data strategy - including metrics, data pipelines, offline logging, and working cadence with cross-functional teams
• Mentored and provided technical guidance to junior data scientists and analysts

San Jose, CA, US

• Advertising technology
• 3rd party programmatic ads yield optimization, pricing strategy and algorithm development
• Built NLP models to understand customer feedback through sentiment analysis and topic modeling
• Built and maintain ETL jobs and automated dashboards for PMs and business partners to track key metrics daily
• Analyzed search page item ranking to guide 1st party Ads (Promoted Listings) product development
• Investigated cannibalization of 1st party Ads on View Item page from A/B test data

San Francisco, CA, US

• Partnered with a startup on building predictive models for vehicle logistics
• Performed geographic segmentation on demand data using Google Maps Distance Matrix API
• Integrated features engineered from time-series data with external signals (e.g. local weather) to build models (Lasso, Random Forest, SVM)
• Delivered production-ready code outputting 7-day forecast, which can help the company to increase the car utilization rate by 45%

San Francisco, CA, US

• Worked in Risk team on improving machine learning models for online fraud detection/mitigation.
• prepared data from HDFS/S3 using Presto/Hive and Python UDFs
• conducted feature engineering for further model training
• prototyped a pipeline to interpret the RF model by observation clustering and feature extraction
• customer segmentation: identified 4 major customer groups and distilled features related to bad actors
• analyzed photo content and extracted meaningful features using Python and Tesseract OCR

Doctor Of Philosophy (Phd), Physics

Bachelor Of Science (B.S.), Physics