Tommaso Pellegrinetti

Welcome to my personal webpage! I am a Data Scientist with three years of experience spanning both industry and academia. Currently, I specialize in pricing analytics at HP, focusing on demand estimation and price optimization. Previously, I contributed to research projects at the intersection of Economics and Machine Learning during my time at the Innocenzo Gasparini Institute for Economic Research (IGIER) at Bocconi University. I hold a Master's degree in Economics with a major in Big Data and Business Analytics from Bocconi University and a Bachelor's degree in Economics from the University of Pisa. On this site, you can explore more about my professional and academic background, as well as my personal interests. Feel free to reach out via email or connect with me on LinkedIn.

• Read CV

Research Experience

During my Master's studies, I became deeply engaged with the economics of digital platforms and the application of computational methods to economic research.

In April 2022, I joined the Innocenzo Gasparini Institute for Economic Research (IGIER) as a Research Assistant under the guidance of Prof. Francesco Decarolis and Prof. Ksenia Shakhgildyan. In this role, I have contributed as a data scientist to empirical research projects in the digital advertising industry.

My research focuses on two main streams:

• Artificial Intelligence in Sponsored Search Auctions
  This work examines the impact of algorithmic bidding on digital platform revenues. Using simulated experiments, we explore how bidders employing different types of Reinforcement Learning algorithms influence auction outcomes.
• Effects of Recommender Systems in Digital Platforms
  For my Master's thesis, I conducted an empirical analysis on the effects of recommender systems on song demand in the context of music streaming platforms. This study explored how algorithmic recommendations influence consumer behavior and demand patterns.

Papers

• Algorithmic Competition and Informational Advantage in Digital Markets: Evidence from Search Auctions (with Francesco Decarolis, Gabriele Rovigatti, Michele Rovigatti, and Ksenia Shakhgildyan) - Work in Progress
  View Abstract
  In this paper, we study the effects of the deployment of proprietary Artificial Intelligence Algorithms (AIAs) by major digital platforms. With advanced algorithms built on superior data, they can easily outperform independent counterparts. This is the main reason why more and more firms delegate their activities to the platforms themselves.
  Focusing on the online advertising market, we provide a comprehensive analysis of the platforms’ data advantage and bid delegation. First, we experimentally demonstrate that an advertiser can gain a significant advantage when utilizing the platform’s services against a less sophisticated competitor, whether through bid delegation or by purchasing the relevant data. Second, we find that the misalignment of incentives between the platform and advertisers favours providing a bidding algorithm over selling data.

Personal Projects

INTRO TO WEB SCRAPING

Explore the fundamentals of web scraping in Python, with a particular emphasis on its applications in economic and business research.

EXPLORE EUROPEAN SALARIES

This data visualization project explores the disttibution of salaries across some of the main European Cities.

ITALY ELECTIONS RESULTS VIZ

Data visualizations on the results of 2022 Italy general election, with a focus on the province of Lucca, where I reside.

UPLIFT MODELING AND CUSTOMER RETENTION

Group project that delved into the applications of uplift modeling for optimizing a customer retention campaign.

• View All Projects

Resources

Here you can find some (hopefully) useful resources:
- Resources for Research Assistants