Stephane Shao

Senior Data Scientist

Etsy

I am …

a senior data scientist at Etsy, who has a genuine love for both Statistics and Machine Learning.

My team sits at the intersection of Data Engineering and Data Science, as we develop new methodologies for online experimentation.

Contact me at: stephaneshao [@] alumni [dot] harvard [dot] edu

I like ...

Bayesian statistics
Causal inference
Machine learning

Research

S. Shao (2022). Mitigating the winner’s curse in online experiments. Code as Craft, Etsy’s Engineering Blog.

S. Shao, C. Burke (2022). Understanding the collective impact of experiments. Code as Craft, Etsy’s Engineering Blog.

S. Shao, L. Ignatovsky, J. Beckley (2022). Imbalance detection for healthier experimentation. Code as Craft, Etsy’s Engineering Blog.

S. Shao, K. Gaan, S. Emanuele, J. Kaushik (2021). Increasing experimentation accuracy and speed by using control variates. Code as Craft, Etsy’s Engineering Blog.

Z. Branson, S. Shao (2021). Ridge rerandomization: an experimental design strategy in the presence of covariate collinearity. Journal of Statistical Planning and Inference, 211, 287-314.

S. Shao (2019). Bayesian model comparison and asymptotics for state-space models. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.

S. Shao, P. E. Jacob, J. Ding, V. Tarokh (2019). Bayesian model comparison with the Hyvärinen score: computation and consistency. Journal of the American Statistical Association, 114 (528), 1826-1837. See also: supplementary material.

Teaching

I have been a teaching assistant at Harvard University for the following courses:

STAT 131 - Time Series and Prediction (Fall 2017)
STAT 213 - Statistical Inference II (Spring 2017)
STAT 210 - Probability I (Fall 2016)
STAT 111 - Introduction to Theoretical Statistics (Spring 2016)
STAT 110 - Introduction to Probability (Fall 2015)