Yuling Feng

About Yuling Feng

Experienced machine learning scientist with successful records of designing, developing, and deploying machine learning products in marketing segmentation, email personalization, content recommendation, E-commerce risk and fraud detection, ROI measurement, medium decomposition, mix medium modeling, sales forecasting. Passionate about applying the latest in ML/DL to solve business problems.

Experience

1. Staff Data Scientist Machine Learning Scientist

   Expedia Group

   Oct 2019 — Present · Austin, TX, US

   Led development of multi-touch attribution models using sequential deep learning with attention mechanisms; demonstrated $5M incremental lift in A/B testing and deployed across major brands and business lines-Led the development of end-to-end Bayesian marketing mix models using MCMC in Python to estimateincremental impact for ~$1B annual marketing spend across various marketing channels; directly influenced corporate marketing allocation- Designed and implemented a modular deep neural network for channel saturation curve estimation — US Patent pending- Created an automated pipeline to calibrate incrementality test results into Bayesian model priors, eliminating manual tuning and improving model robustness- Led the end-to-end deployment of a personalized marketing content recommendation engine (XGBoost + DNN), including feature engineering, model training, validation, deployment, and stakeholder collaboration.

Education

• Sun Yat-sen University

  Bachelor, Statistics

• University of South Carolina

  PhD, Statistics

  2013

• The University of Hong Kong

  Exchange program, Statistics