Gianluca Francone
About Gianluca Francone
Gianluca Francone is a Data Scientist currently employed at Priogen Energy in Amsterdam, where he has worked since 2020. He holds a Master of Science in Data Science from the Universiteit van Amsterdam and has a background in Operations Research and Engineering Management from Università La Sapienza di Roma.
Work at Priogen Energy
Gianluca Francone has been employed at Priogen Energy since 2020, where he serves as a Data Scientist. His role involves developing and maintaining forecasting models for the Research and Development department. Prior to his current position, he worked as a Data Specialist at Priogen Energy from 2018 to 2020, contributing to various data-driven projects in the Amsterdam Area. His experience at Priogen Energy spans a total of four years in the Amsterdam, North Holland region.
Education and Expertise
Gianluca Francone holds a Master of Science in Data Science from the Universiteit van Amsterdam, which he completed in 2018. He also earned a Master's degree in Operations Research from the Dipartimento di management at Università La Sapienza di Roma, where he studied from 2014 to 2017. Earlier, he obtained a Bachelor's degree in Engineering/Industrial Management from the same institution, studying from 2010 to 2014. Additionally, he studied at FEP - Faculdade de Economia da Universidade do Porto for one year in 2016. His educational background equips him with expertise in resource allocation for modern scientific international environments.
Internship Experience
In 2018, Gianluca Francone completed a four-month internship at Door2doc BV in the Utrecht Area, Netherlands. This internship provided him with practical experience in the data science field and contributed to his professional development prior to his roles at Priogen Energy.
International Travel and Relocation
Gianluca Francone is open to international travel and relocation opportunities to enhance his professional development. This willingness indicates his commitment to expanding his expertise and gaining diverse experiences in the field of data science.