• Develop and maintain marketing models that score customers’ conversion propensity on a bi-monthly basis.
• Manage model risks through active model monitoring. Address potential model errors or drifts.
• Contribute to building a culture of experimentation by advising business teams on A/B testing best practices. Collaborate with business partners to refine experimental designs. Build tools to enable appropriate statistical tests and power analysis for stakeholders.

• Partnered across multiple institutions to deliver a machine learning pipeline for estimating the abundance of endangered North Pacific whales with acoustic recordings from the sub-Arctic.
• Improved and automated the existing abundance estimation process by developing CNN models that extract whales’ “gunshot” calls.

• Partnered with the Department of Anesthesiology to deliver a machine learning solution to estimate the expected opioid dosages for various medical procedures.
• Identified abnormal opioid dosages and flagged at-risk healthcare providers using the resulting model.
• Led the effort in identifying and removing outliers in multi-year medical records in collaboration with medical professionals. Redesigned the feature engineering process to reduce data dimension. Improved model r-squared by 30%.

• Mentored graduate students' projects in applied statistical inference and statistical learning.
• Held weekly office hours. Responded to student questions on course forums. Graded assignments and projects.

• Led the effort of defining and measuring gaming behaviors in incentive marketing campaigns.
• Collaborated with cross-functional teams to gather information and ensure data integrity in the collection process and downstream analysis.
• Prototyped propensity models for identifying potential gamers using Databricks, Snowflake, and Scikit-Learn.
• Communicated insights to business partners and stakeholders by incorporating principles of data storytelling and interpretable machine learning.

As a member of an early-stage start-up, I actively involved in all aspects of the business and helped to estalish common practices and guidelines in data analytics. My main efforts include:

• Initiated the movement from Excel to R, which significantly expedited the data analysis process and the rotation table designing process.

• Discovered discrepancies and errors in the consumer study database, cleaned the existing database, and enhanced the data collection process to ensure accuracy and efficiency.

• Analyzed product data and extracted product insights by employing inferential statistical testing and data visualization. Innovated the analysis for text data by introducing sentiment analysis in Natural Language Processing.

• Led report writing to communicate findings and business recommendations to clients, including Fortune 500 companies. Delivered workshops regularly to train interns in adequate statistical and programming skills.