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Senior Data scientist | PhD in Physics | AI consultant | Divulgatore scientifico
PhD in Physics skilled in Data Analysis, Machine Learning, coding (mostly in Python) and Mathematical models. Presently I am working as Senior Data Scientist at GSK (with italian "Quadro" qualification), focusing on: -development of mathematical models and an epidemiological repository that will facilitate the assessment of different vaccines in terms of their likely impact on Antimicrobial resistance (AMR) - supporting the data science team in analyzing data and building machine learning algorithms Previously I worked as Data Scientist at Apheris, focusing on the development and optimization of Federated Machine Learning algorithms based on Neural Networks. Apheris enables the secure analysis of data across organizations while keeping proprietary information private. In the past 6 years I worked as Scientist, in the field of Astroparticle Physics (from 2014 to 2017 at Gran Sasso Science Institute, from 2017 to 2020 at Deutsches Elektronen-Synchrotron), publishing more than 20 papers on international peer reviewed journals. From March 2020 to August 2020 I was also involved in research concerning the COVID19 pandemic, becoming Scientific collaborator of Covstat.it, in which data analysis and predictions on the spread of the pandemic have been presented. I speak Italian as native language, I am fluent in English and I have an intermediate knowledge of German. I have also an artistic side, I play piano and I play chess ! Concerning the data science background, I have solid expertise in Machine Learning (scikit-learn package in Python), especially in Neural Networks (mostly Keras-Tensorflow packages plus basic knowledge of Pytorch). I developed my first Neural Network algorithm working at Micron Technology in 2011, during my bachelor thesis in Physics. I have strong expertise concerning the tools required for data science, such as data analysis and data manipul
DataCamp
Machine Learning Scientist with Python
January 1, 2020 – January 1, 2020
DataCamp
Data Scientist, Data Scientist with Python Track
January 1, 2019 – January 1, 2019
GSSI - Gran Sasso Science Institute
Doctor of Philosophy - PhD, Astroparticle Physics
January 1, 2014 – January 1, 2017
Università degli Studi dell'Aquila
Master of Science - MS, Physics
January 1, 2011 – January 1, 2014
Università degli Studi dell'Aquila
Bachelor of Science - BS, Physics
January 1, 2008 – January 1, 2011
Hanover University of Music, Drama and Media
Erasmus project, Piano and chamber music
January 1, 2006 – January 1, 2007
Conservatorio "L.Perosi" di Campobasso
Diploma di pianoforte
January 1, 1996 – January 1, 2006
GSK
Senior Data Scientist
June 1, 2022 – Present
Siena, Toscana, Italia
Apheris
Data scientist
September 1, 2020 – May 1, 2022
Berlino, Germania
Apheris
Data scientist (freelancer)
March 1, 2020 – August 1, 2020
Berlino, Germania
CoVStat_IT
Scientific Collaborator
March 1, 2020 – August 1, 2020
DESY
Postdoctoral Researcher
November 1, 2017 – August 1, 2020
Zeuthen (Berlin)
Micron Technology
Internship
September 1, 2011 – December 1, 2011
Avezzano
Deep Learning in Python
DataCamp
June 23, 2026 – Present
Feature Engineering for NLP in Python
DataCamp
June 23, 2026 – Present
Preprocessing for Machine Learning in Python
DataCamp
June 23, 2026 – Present
Clustering methods with Scipy
DataCamp
June 23, 2026 – Present
Importing Data in Python (Part 1)
DataCamp
June 23, 2026 – Present
Conda Essentials
DataCamp
June 23, 2026 – Present
Introduction to Shell for Data Science
DataCamp
June 23, 2026 – Present
Manipulating DataFrames with pandas
DataCamp
June 23, 2026 – Present
Analyzing Police Activity with pandas
DataCamp
June 23, 2026 – Present
Import data in Python 2
DataCamp
June 23, 2026 – Present
Intro to SQL for Data Science
DataCamp
June 23, 2026 – Present
Interactive Data Visualization with Bokeh
DataCamp
June 23, 2026 – Present
Introduction to Data Visualization with Python
DataCamp
June 23, 2026 – Present
Introduction to TensorFlow in Python
DataCamp
June 23, 2026 – Present
Statistical Thinking in Python (Part 2)
DataCamp
June 23, 2026 – Present
Statistical Thinking in Python (Part 1)
DataCamp
June 23, 2026 – Present
Introduction to PySpark
DataCamp
June 23, 2026 – Present
Image processing in Python
DataCamp
June 23, 2026 – Present
Dimensionality reduction in Python
DataCamp
June 23, 2026 – Present
Extreme Gradient Boosting with XGBoost
DataCamp
June 23, 2026 – Present
Introduction to Portfolio Analysis in Python
DataCamp
June 23, 2026 – Present
Joining Data in SQL
DataCamp
June 23, 2026 – Present
Network analysis in Python
DataCamp
June 23, 2026 – Present
B1 online certificate of German Language
Busuu
June 23, 2026 – Present
Unsupervised learning in Python
DataCamp
June 23, 2026 – Present
Data scientist with Python track
DataCamp
June 23, 2026 – Present
Matlab Onramp
MathWorks
June 23, 2026 – Present
Feature Engineering for Machine Learning in Python
DataCamp
June 23, 2026 – Present
Linear Classifiers in Python
DataCamp
June 23, 2026 – Present
Introduction to Relational Databases in SQL
DataCamp
June 23, 2026 – Present
Pandas Foundation
DataCamp
June 23, 2026 – Present
Intermediate Python for DataScience
DataCamp
June 23, 2026 – Present
Machine Learning Onramp
MathWorks
June 23, 2026 – Present
Winning a Kaggle Competition in Python
DataCamp
June 23, 2026 – Present
Introduction to Natural Language Processing in Python
DataCamp
June 23, 2026 – Present
Model Validation in Python
DataCamp
June 23, 2026 – Present
Image Processing with Keras in Python
DataCamp
June 23, 2026 – Present
Machine Learning for Time Series Data in Python
DataCamp
June 23, 2026 – Present
AppQuality Tester
UNGUESS
June 23, 2026 – Present
Machine Learning with Tree-Based Models in Python
DataCamp
June 23, 2026 – Present
Merging DataFrames with pandas
DataCamp
June 23, 2026 – Present
Cleaning data in Python
DataCamp
June 23, 2026 – Present
Machine Learning with the Experts: School Budgets
DataCamp
June 23, 2026 – Present
Supervised Learning with scikit-learn
DataCamp
June 23, 2026 – Present
Python Data Science Toolbox (Part 2)
DataCamp
June 23, 2026 – Present
Python DataScience Toolbox (Part 1)
DataCamp
June 23, 2026 – Present
Introduction to Python
DataCamp
June 23, 2026 – Present
Hyperparameter Tuning in Python
DataCamp
June 23, 2026 – Present
Advanced Deep Learning with Keras
DataCamp
June 23, 2026 – Present
Introduction to Deep Learning with Keras
DataCamp
June 23, 2026 – Present
Cultural Fit Analysis
The candidate's background shows a strong inclination towards research and complex problem-solving, which aligns well with roles requiring deep analytical capabilities. The diverse experience, from academic research to industry roles in pharmaceuticals and AI startups, indicates adaptability. However, the target role is 'Data Analyst' while the candidate's experience is predominantly 'Data Scientist' with a strong focus on advanced ML/DL. This suggests a potential mismatch in the depth of technical work expected versus the candidate's senior data science expertise. The lack of explicit project details beyond job descriptions makes it difficult to fully assess project diversity and specific contributions.
Soft Skills & Operational Fit
The candidate's extensive academic and professional background suggests strong analytical thinking, problem-solving, and research skills. The transition from astroparticle physics to data science indicates adaptability and a drive for continuous learning. Experience in collaborative machine learning (federated learning) implies an ability to work in complex, multi-stakeholder environments. However, without psychometric test results, specific insights into work attitude, stress handling, and team collaboration are unavailable.