Jimmy Jin


Data Scientist

Stripe July 2019 - Present
  • Optimizations on the Payment Intelligence team. Previous stints on Treasury and Payment Acceptance.

Volunteer Data "Engineer"

Vote By Mail 2020 Jun 2020 - Dec 2020
  • Managed ingestion and pipelining of voter data using Airflow/S3/Redshift.


Optimizely Nov 2017 - May 2019
  • Responsible for all statistics operations at Optimizely and assumed acting Product Manager duties for the Analytics team in Feb 2019.
  • Created Epoch Stats Engine, a novel stratification-based estimator for sequential testing designed to eliminate "Simpson's Paradox" due to dynamic traffic allocation. Blog post, Technical writeup
  • Authored Optimizely's first-ever Statistics Roadmap, outlining the company's statistics short- and long-term strategy for statistics R&D.

Selected projects

Epoch Stats Engine

  • Joint work with Leo Pekelis at Optimizely.
  • We developed a new estimator to make A/B testing compatible with dynamic traffic allocation policies such as those induced by a multi-armed bandit algorithm. The estimator is based on a simple stratification idea that is simple to implement, requires minimal assumptions, and is compatible with most central limit theorem-based methods.
  • Blog post: https://blog.optimizely.com/2018/11/27/stats-accelerator-acceleration-time-varying-signals/

Change point detection in Network models: preferential attachment and long range dependence

  • To appear in Annals of Applied Probability.

    We developed a changepoint variant of preferential attachment and then showed how to detect the changepoint using a functional central limit theorem for the number of leaves in the graph. Along the way we also proved an interesting result regarding the effect of the changepoint on the exponent of the degree distribution. This paper forms the bulk of my dissertation.


PhD Statistics (2017)

BA Economics (2010)


Very knowledgeable

Some production work