I graduated in 2017 with a MSc in Computer Engineering at the University of Pisa.
During the academic courses I have been given a wide-range education and, in particular while preparing projects of Data Mining, Artificial Intelligence, Deep Learning, Statistics and obviously the Thesis.
The Master Thesis revolved around the design and implementation of a framework that allows the characterization, profiling and clustering of city areas based on data from of activities, points of interest, social dynamics, real estate ads, local news information, and open dataset.
After the graduation, I worked at the Data Science and Engineering Lab at the Department of Information Engineering of the University of Pisa as a Data Scientist Researcher on the extension of the master thesis project to other cities and data sources.
From 2018 until now, I’m working as Data Scientist in Eni Digital Unit.
In Eni, I was involved in different projects concerning the development of Advanced Analytics models for Upstream Plants, Refineries, Supply and Logistic Unit, HSE and HR. These projects covered a lot of topics like predictive maintenance, root cause analysis, anomaly detection and Natural Language Processing.
My job is about the end-to-end development of Advanced Analytics solutions starting from the framing of business problems (e.g supporting the business user in the initial Workshops of Design Thinking), the development and test of the solutions and then the support to industrialization of them to the production environment.
I also had the opportunity to present several of these projects in international conferences: ADIPEC Conference in Abu Dhabi, the Digital Refining Summit in London, the SPE Norway One Day Seminar in Bergen (Norway), and the Offshore Mediterranean Conference, in Ravenna (Italy).
Our Eni’s colleagues challenged us: we believe we have enough data to build an AI digital product. We shaped an internal team combining different competences to face the challenge and we brought together Designers, Data Scientists and IT business partner. We accepted the challenge and we engage them in a quick path of 3 Design Thinking workshops with different goals each time to finally being able to design a proto-user experience based on their data, previously checked on quality and accessibility. Once the concepts were rationalized with supporting data, we were able to understand together where to start to going deep into data and develop a prototype to already augment their capabilities into their daily job.