Paolo Pagnottoni

CURRENT

Assistant professor of Statistics, Department of Economics and Management, University of Pavia (Italy) (since March 2022)

Consulting experience in the banking Industry and national and international institutions. Skilled in Statistical and Econometric Modeling, with background in programming. Main areas of interest: Computational Statistics, Financial Data Science, Financial Networks, Financial Markets, Cryptocurrency Markets, Financial Econometrics, Pricing

Linkedin:  https://de.linkedin.com/in/paolo-pagnottoni-822609148 

Mail to: paolo.pagnottoni@unipv.it

EXPERIENCE

Research Fellow in Statistics, Department of Economics and Management, University of Pavia (Italy)  (January 2021 - February 2022)

Research Fellow in Management Engineering, Department of Management Engineering,  Politecnico di Milano (September 2020 - December 2020)

Research Fellow in Statistics, Department of Economics and Management, University of Pavia (January 2019 - September 2020)

Visiting Research Fellow, University College London, United Kingdom (March 2020 - May 2020)

Data Analyst and Modeler at Credito Valtellinese, Milan/Sondrio, Italy  (October 2017 - December 2018)

TEACHING

Assistant Lecturer in Big Data Analysis, Department of Economics and Management, University of Pavia, AY 2018/2019 (Master level)

Assistant Lecturer in Statistica L-Z, Department of Economics and Management, University of Pavia, AY 2017/2018 (Undergraduate level)

Lecturer and Coordinator of the Data Science course, Young Talent in Action Program , Manpower group  (June 2018 - October 2019)

EDUCATION

University of Bergamo and University of Pavia (Italy) [ENG]

PhD, Applied Economics and Management - Chair of Statistics (2021)

University of Tübingen (Germany) [ENG]

Master's Degree, European Economics - Finance and Econometrics  (2017), with honours

University of Pavia (Italy) [ENG]

Master's degree, Economics and Finance  (2017), with honours

University of Milan - Bicocca  (Italy) [IT]

Bachelor's degree, Economics and Business Administration - Economics, Statistics and Computer Science for the Enterprise (2015)