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Portfolio Manager, Quantitative Analyst
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
• Portfolio manager with a strong quantitative background (electronic engineering, statistics, signal processing), and a deep interest in tackling real-world problems with machine learning tools and methods. • Experience on quantitative finance topics: asset allocation, portfolio optimization, financial time series analysis, statistical methods/machine learning applied to equity portfolio construction. • Skilled programmer, with solid knowledge of software engineering concepts and practices, and experience in rapidly producing and validating both proof-of-concept and production quality software from either academic papers or high level specifications.
Università Bocconi
Master, Quantitative Finance and Risk Management
January 1, 2008 – January 1, 2009
Politecnico di Milano
Laurea (MSc), Telecommunications Engineering
January 1, 1996 – January 1, 2004
MEDIOBANCA SGR
Portfolio Manager
October 1, 2016 – Present
Kaggle (participant)
Machine Learning Competitions Participant
January 1, 2013 – Present
Banca Esperia
Portfolio Solutions Quantitative Analyst
January 1, 2011 – September 1, 2016
Milan
Unicredit
Market Risk Methodologies & Architecture
September 1, 2009 – January 1, 2011
Greater Milan Metropolitan Area
Banca IMI
Intern - Fixed Income Trading
January 1, 2009 – January 1, 2009
Milan, Lombardy, Italy
Politecnico di Milano / WisyTech
System Engineer / Project Lead
June 1, 2006 – September 1, 2008
Greater Milan Metropolitan Area
Politecnico di Milano
Research Grant
January 1, 2004 – January 1, 2007
Milan, Italy
Nalux
Intern - R&D Development
January 1, 2002 – August 1, 2002
Osaka, Japan
AXA Driver Telematics Analysis competition
March 1, 2015 – Present
Top 10% finish in a data science competition, with the goal of using GPS telemetry data to discriminate car drivers.
GMAT (770, 99% Percentile)
GMAC
June 24, 2026 – Present
Introduction to Apache Spark
edX
June 24, 2026 – Present
Big Data Analysis with Apache Spark
edX
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Probabilistic Graphical Models
Coursera
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily weighted towards finance and telecommunications engineering, with a strong quantitative and analytical focus. While the 'Data Analyst' target role aligns with their analytical skills, the depth of experience in traditional finance roles might require an assessment of their adaptability to a pure tech-driven data analysis environment. The Kaggle participation and certifications in Spark and Machine Learning indicate an interest in modern data practices, which is a positive for cultural fit.
Soft Skills & Operational Fit
The candidate's experience as a Project Lead and in mentoring teammates suggests leadership and collaboration skills. Their participation in competitive data science indicates a proactive and problem-solving attitude. The diverse roles from system engineering to portfolio management suggest adaptability and a broad operational understanding.