Jan 2022 – Jan 2026 · 4 yrs

• lead and grow a strong team of machine learning scientists that design, build, deploy, and operate scalable ML solutions to combat fraud in retails, gift card and healthcare
• Create vision and strategy to ensure the team delivers exceptional results in both technology and business outcome with customer obsess

Jul 2021 – Jan 2022 · 6 mos

Apr 2019 – Jun 2021 · 2 yrs 2 mos

• Develop machine learning systems for fraud detection in Amazon online retail, protect Amazon customers from fraudsters and make Amazon the safest place in the world

Nov 2017 – Mar 2019 · 1 yr 4 mos

• Led descriptive and predictive analysis of customer growth and retention, deriving insights for business strategies and operational innovations
• Automated workflows, productionized machine learning models and created a self-serviced UI for non-technical managers to make real-time predictions with new observations

May 2017 – Aug 2017 · 3 mos · Greater New York City Area

• Created a web app to predict the success of online petitions and help petitioners draft better appeals, using Python, Flask, Twitter Bootstrap and hosted with AWS
• Built a predictive model for number of signatures using NLP, dimensionality reduction from petition texts scraped from change.org

May 2016 – Aug 2016 · 3 mos · Fremont, California

• Performed statistical and machine learning analysis of service and reliability metrics (e.g. service center pressure, fleet reliability) and communicated with other Tesla departments to understand business problems and apply solutions
• Designed, optimized and implemented a recommendation algorithm for body shop part purchases, greatly reducing the customer waiting time for repairs
• Built and maintained a web app for mapping Tesla electricians worldwide using Rshiny, which allowed managers to monitor the status of electricians in real-time

Jun 2015 – Nov 2015 · 5 mos · New Brunswick, NJ

• Built nonlinear models for J-curve relationships between physiological indices and hazard ratio and provided a better understanding of how pulse pressure and BMI relate to health/mortality (published in Circulation)
• Project on big data and precision medicine: designed prototype algorithms to build personalized disease networks (PDNs) based on hospitalization records, which revealed the disease evolution for individual patients. I developed new methodology to cluster PDNs for better predictions of clinical outcomes (Package published on CRAN)

Sep 2012 – Sep 2015 · 3 yrs · Piscataway, NJ

• Discovered and characterized novel RNA modification, which uncovered new domains of RNA research and provide a better understanding of RNA-level biological regulation in neuron development and behavior (Science 2016)