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Research Scientist 2 - Microsoft
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
My fields of interest include Neural Networks, Machine Learning, Optimization and Applied Mathematics. The Master's degree in Mathematics and the Doctorate in Computer Science gave me the opportunity to develop transversal knowledge in different fields. This, combined with my passion for research and the ability to adapt without too much difficulty to new contexts, allow me to deal comprehensively and efficiently with different work situations.
Università degli Studi di Torino
Doctor of Philosophy - PhD, Computer Science
January 1, 2014 – January 1, 2017
Università degli Studi di Torino
Laurea Magistrale LM, Dipartimento di Matematica
January 1, 2011 – January 1, 2013
Università degli Studi di Torino
Laurea triennale, Dipartimento di Matematica
January 1, 2008 – January 1, 2011
Liceo Scientifico G. Segrè
Maturità P.N.I.
January 1, 2003 – January 1, 2008
Microsoft
Applied Scientist 2
August 1, 2023 – Present
Italia
Nuance Communications
Sr. Research Scientist
March 1, 2017 – July 1, 2023
Torino, Italia
Université Pierre et Marie Curie
Traineeship
March 1, 2015 – July 1, 2015
Parigi, Francia
Università degli Studi di Torino
Ph.D.
January 1, 2014 – February 1, 2017
Torino, Italia
SiTI - Istituto Superiore sui Sistemi Territoriali per l'Innovazione
Traineeship
March 1, 2013 – September 1, 2013
Torino, Italia
Microsoft Global Hackathon 2025
Microsoft
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards research and applied science in AI/ML, particularly in healthcare. While this demonstrates a strong technical foundation, the target role of 'Data Analyst' might not fully align with their advanced research expertise. The lack of diverse project experience outside of AI/ML research and academic settings could indicate a narrower scope of interest or experience compared to a typical data analyst role that often requires broader business domain understanding and diverse analytical toolsets. The certifications are relevant to ML but do not broaden the scope for a general data analyst role.
Soft Skills & Operational Fit
The candidate's resume highlights a strong research background and experience in complex problem-solving, which suggests good analytical and critical thinking skills. However, without specific project details or interview data, it is difficult to assess collaboration, leadership, or communication in an operational context. The focus on research and applied science roles indicates a preference for innovation and technical depth.