Giovanni Antinucci, PhD
About Giovanni Antinucci, PhD
Giovanni Antinucci, PhD, is an Associate Director and Internal Consultant at UBS in Zurich, Switzerland, where he has worked since 2020. He has a strong background in machine learning, AI, and data science, with previous research roles at the University of Geneva and the University of Zurich.
Work at UBS
Giovanni Antinucci serves as an Associate Director and Internal Consultant at UBS since 2020. In this role, he focuses on computational techniques and algorithms, contributing to the firm's Quant Hub within the Digital Practice. His responsibilities include applying machine learning, artificial intelligence, and data science to enhance quantitative analysis and statistical modeling. Antinucci has gained hands-on experience in compliance and liquidity management during his tenure at UBS, which has further solidified his expertise in the financial sector.
Education and Expertise
Giovanni Antinucci holds a Doctor of Philosophy (PhD) in Mathematics from Università degli Studi di Roma Tre, which he completed from 2013 to 2017. He also earned a Master's degree in Theoretical and Mathematical Physics from Sapienza Università di Roma between 2011 and 2013, and a Bachelor's degree in Physics from the same institution from 2008 to 2011. His academic background provides a strong foundation for his expertise in machine learning, artificial intelligence, and data science.
Background
Antinucci has a diverse academic and professional background. He worked as a Postdoctoral Researcher at the University of Zurich from 2017 to 2019 and at the University of Geneva for seven months in 2020. Prior to these roles, he was a Mathematics Tutor at Università degli Studi Roma Tre from 2014 to 2016, where he also completed his PhD studies. His experience spans various academic institutions and roles, contributing to his comprehensive understanding of quantitative analysis.
Achievements
Throughout his career, Giovanni Antinucci has developed a robust skill set in quantitative analysis and statistical modeling. His work at UBS has involved applying advanced computational techniques to real-world financial challenges. He has been instrumental in projects that leverage machine learning and AI to improve decision-making processes within the organization. His academic research and professional experiences have positioned him as a knowledgeable figure in the fields of data science and internal consulting.