Serve as a mentor and consultant to the Board of Directors at Student Echo (https://www.student-echo.org), a non-profit organization. My role is to provide expert guidance, share insights, and offer strategic advice based on my experience and knowledge in Data Science, Machine Learning, and AI.

Collaborate with the manager of machine learning scientist team and lead the team in building Expedia Group next generation recommender models in various lines of business (hotel, vacation rental, flight, car rental, activities etc.).

1. Lead key technical data science projects delivering successful outcomes for e-commerce technology domains.2. Ensure data science and machine learning models and systems deliver high-quality outputs that result in measurable positive impact to topline and bottomline objectives.3. Act as a technical consultant to the head of data science for e-commerce and other e-commerce technology leaders and help develop ML/AI strategy.4. Perform and run individual/group model/code reviews to ensure ML solutions are optimized and team continuously evolves its output quality.5. Act as a spokesperson for model development and maintenance best practices.6. Engage and support company-wide data science community for ongoing learning, training, meetings, speaking engagements, alignment and orchestration.7. Follow relevant publications in the industry and bring novel modeling approaches to the team.

1. In charge of Gross Booking Volume and risky transactions review volume forecasting and optimization using Facebook Prophet2. Led Booking squad machine learning scientists in design, development, and operation of the fraud risk modeling across all Expedia Group brands including Expedia.com, Hotels.com, Expedia Affiliate Network, Vrbo.com, Hotwire.com, Travelocity.com, Orbitz.com, and CarRentals.com.3. Partnered with the ML engineering team on weekly fraud model production releases and model retraining4. Designed data quality metrics for offline data quality monitoringContribution: already 5X industry standards; Protected $800M fraud loss across EG brands per year

Collaborated with other data scientists and developed the 2nd/3rd generations of Fraud models using GBM/XGBoost algorithm and an ensemble approach with lift 19% (saved the company $41 million per year); prevented 98% ($1.4 billion in year 2018, for example) of attempt fraud with attempt fraud rate 1.1% and auto-reject & manual review rate 1.8%

Designed and developed the first generation of online Card-Not-Present (CNP) fraud risk scoring models using logistic regression; prevented 80% ($1.2 billion per year) of attempt fraud

1. Conducted monthly payoffs and retention analysis for prime and sub-prime home loans2. Deep dived post-campaign analysis to support home loan team

1. Developed price-elasticity models, deposits balance attrition models, and short range time series forecasting models for over 50 billion dollars of products (Platinum Checking, Platinum Savings, and Money Market Savings)2. Provided price suggestions and customer insights for product promotion and customer retention3. Interacted directly with product managers to optimize price and maximize spread income4. Trained and guided junior statisticians to solve advanced statistical problems

Analyzed the stock market; forecast stock prices; provided consulting services to customers