Lorenzo Meninato
About Lorenzo Meninato
Lorenzo Meninato is a Data Scientist at the Federal Reserve Bank of New York, where he has worked since 2018. He has a strong academic background in Statistics, Economics, and Computer Science, complemented by experience in private equity and teaching assistance.
Work at Federal Reserve Bank of New York
Lorenzo Meninato currently serves as a Data Scientist at the Federal Reserve Bank of New York, a position he has held since 2018. In this role, he applies data science techniques to support various analytical projects. He previously interned at the same institution for two months in the summer of 2017, gaining initial experience in a professional setting.
Teaching Experience at Haverford College
From 2016 to 2018, Lorenzo worked as a Teaching Assistant at Haverford College. During this two-year period, he supported faculty in delivering course content and assisted students in understanding complex topics, contributing to the academic environment of the college.
Educational Background
Lorenzo Meninato holds a Bachelor of Science in Economics from Haverford College, where he studied from 2014 to 2018. He furthered his education at New York University, earning a Master of Science in Computer Science from 2019 to 2022. Additionally, he studied Statistics at the University of Pennsylvania for one year, from 2017 to 2018.
Experience in Private Equity Analysis
Prior to his role at the Federal Reserve, Lorenzo worked as a Private Equity Analyst at Bryn Mawr Capital Management from 2012 to 2016. His four years in this position involved analyzing investment opportunities and contributing to the firm's financial strategies.
Technical Skills and Projects
Lorenzo has developed an interactive version of a time series shock model using R Shiny, incorporating dygraphs and ggplot2 for data visualization. He has experience working with kdb+, an in-memory database, for data science applications. Additionally, he utilized Rcpp to enhance the performance of stress test models, significantly reducing computation time. His expertise also includes developing NLP models and automating reporting processes using Python.