Greetings! I’m a machine learning engineer with Meta’s Reels recommendations team. Among the various projects I’ve been involved in, I have been leading:

Prior to Meta, I led the modeling team within Walmart’s Customer org, where I spearheaded the development of customer-centric data science and machine learning solutions. These initiatives were designed to enhance Walmart’s customer lifetime value and increase the share of wallet. I was also one of the founding data scientists for Walmart’s membership program, Walmart+, and built ML models on Walmart+ customer acquisition, conversion, retention, reactivation, and lifetime value for making informed marketing decisions.

My early career was on quantitative financial research, where I contributed my expertise to renowned institutions such as Goldman Sachs, J.P. Morgan, and Deutsche Bank. My roles encompassed the intricate realm of rates pricing models, and market-making algorithms for Treasuries and corporate bonds.

I received PhD in Statistics from Department of Statistics at Rutgers University, New Brunswick, advised by Professor Minge Xie and Professor Regina Y. Liu, and BSc in Statistics from University of Science and Technology of China.

 

Education

Ph.D., Department of Statistics, Rutgers University, Oct 2017.

BSc, Department of Statistics and Finance, University of Science and Technology of China, June 2012.

 

Experiences

Staff Software Engineer, Machine Learning at Meta, Apr 2021 to present.

Senior Manager I, Data Science at Walmart, Jan 2020 to Apr 2021.

Associate, Fixed Income Strats at Deutsche Bank, Dec 2018 to Dec 2019.

Associate, Quantitative Research at Goldman Sachs, Jun 2017 to Dec 2018.