Matteo Centonze

Matteo Centonze has a diverse work experience in the field of data science and engineering. Matteo is currently working as a Data Scientist at Kitman Labs since 2022. Prior to this, they worked at Stellantis as a Data Scientist, where they led and coordinated the Data Science team within the Software Factory. In this role, they mentored junior team members, collected and analyzed requirements from business units, and supported the business with custom analysis and data extractions. Matteo also continued to contribute as a lead developer on various data science and data engineering projects, including the development of a simulation tool for product configuration optimization and a customer segmentation pipeline.

Before joining Stellantis, Matteo worked as a Data Scientist Consultant at Sysdata S.p.A. from 2019 to 2020. Prior to that, they held a Research Fellowship at the Università degli Studi di Roma 'La Sapienza', where their research focused on the implementation and testing of advanced technologies for controlled indexing of archival digital resources. Matteo worked on parsing and cleaning poor-quality pdf documents, extracting and filtering named entities, and applying complex networks theory for historical reconstruction.

Matteo also gained experience during an internship at Consiglio Nazionale delle Ricerche, where they worked on a thesis project evaluating a transfer learning approach for predicting human mobility patterns. Additionally, they worked as an internship role at RJC Soft S.r.l. as a Computer Vision/Deep Learning Software Engineer, where they developed a video analysis system for security, transport, and service planning purposes. Matteo gained proficiency in computer vision libraries, image filtering and analysis, and state-of-the-art deep learning technologies.

Earlier in their career, Matteo worked as a Patent Analyst at Istituto Italiano di Tecnologia, where they assessed the patentability requirements of invention proposals and conducted prior art searches in optics, microscopy, smart materials, and rehabilitation robotics.

Overall, Matteo Centonze has a strong background in data science and engineering, with expertise in various domains such as healthcare, automotive, and digital archiving.

Matteo Centonze has a diverse educational background in the field of physics and data analytics. Matteo obtained their high school diploma from Liceo Scientifico in the year 2010. Matteo then pursued a bachelor's degree in Physics from Università degli Studi di Torino, graduating in 2013. Matteo went on to complete their master's degree in Physics of Complex Systems from the same university, finishing in 2015.

In 2018, Matteo enrolled in Università di Pisa for a postgraduate master's degree in Big Data Analytics and Social Mining, which they completed in 2019. Alongside their formal education, Matteo also obtained several certifications to enhance their skills. In 2016, they completed the DL-101: General Course on Intellectual Property from the World Intellectual Property Organization (WIPO). Additionally, in 2018, Matteo obtained certifications in Advanced Computer Vision with Tensorflow and Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs from Udemy. Most recently, in 2022, they acquired the Professional Scrum Master I (PSM I) certification from Scrum.org.