About

David Puldon is a Machine Learning Engineering Lead for the Cash App Banking ML and Identity ML teams at Square. He has a strong background in Risk and Experimental Particle Physics. David is a Fellow in the Insight Data Science program that helps PhDs transition into Data Scientist Roles in Industry. He is also the creator of Game2Table.xyz, a recommendation app that recommends board games to buy that your entire gaming group would enjoy. David has utilized the boardgamegeek.com API to collect rating/ownership data on 60,000+ users and 11,000+ board games. He parsed the data using Python and stored it in MySQL. He performed an item-based collaborative filtering algorithm on user/group game ratings and purchase histories to recommend future purchases. David created the front end using Twitter Bootstrap, Flask to interface with the Python/MySQL back end and AWS to host the website. Prior to joining Cash App, David was a Data Science Lead, Operations at Square. He was a particle physicist and member of the ATLAS collaboration, an organization of 3000+ physicists and engineers responsible for the construction/operation/analysis of the ATLAS particle detector located at the Large Hadron Collider in CERN, Switzerland. He was the lead analyzer of a 5 person international analysis team resulting in a publication of the electroweak diboson semi-leptonic cross section measurement. David maintained and updated the analytical framework on local computing cluster, using Python, ROOT, and C++, to analyze 75+ TBs of data collected from the ATLAS detector. He utilized statistical methods including regression analysis, likelihoods, confidence intervals, frequentist statistics, error estimation, monte carlo simulations, and correlations to analyze and interpret particle collision data. He presented at weekly meetings to the analysis team as well as regularly to the larger scientific ATLAS collaboration. David also conducted sensor quality studies on pixel detector sensors and performed data cleaning on offline data streams from the ATLAS pixel detector. David holds a Doctor of Philosophy (Ph.D.) in Physics from Stony Brook University and a Bachelor of Science (B.S.) in Physics from Florida International University. His technical skills include ML, Data Scientist, Python, MySQL, AWS, Research Scientist, Flask, Frontend, Backend. David has 8.03 years of relevant experience.