Giovanni Manlio Garofalo

👋 Hi, I'm Giovanni Manlio Garofalo

Data Scientist & Data Analyst passionate about transforming complex data into actionable insights. With expertise in statistical modeling, machine learning, and financial analysis, I bridge the gap between academic theory and practical business solutions.

🔬 Core Expertise

• Credit Risk Modeling: Probit Regression, LDA, ROC curves
• Financial Risk Management: Merton Model, KMV approach, VaR analysis
• Time Series Analysis: ARIMA, GARCH, TRAMO SEATS
• Machine Learning & Big Data: Classification, predictive analytics, pattern recognition
• Statistical Methods: Classical, Bayesian & non-parametric approaches

🛠️ Technical Stack

• Languages: R, Python, MatLab
• Databases: MySQL, Microsoft Access
• Focus Areas: Financial modeling, portfolio management, Data analysis, Data Science, Credit scoring models, Time series forecasting

📊 Featured Projects

Explore my GitHub repositories to find projects showcasing:

• Machine learning applications in finance
• Big data visualization techniques
• Business-Statistics

🌱 Current Focus

I'm currently expanding my expertise in:

• Advanced portfolio management & backtesting
• Stochastic processes in financial modeling
• Machine learning applications for business cases

🤝 Let's Connect

Paesano S.r.l. Statistical Consultant July 2024 - September 2024

 • Conducted comprehensive financial analysis and benchmarking against sector-specific KPIs, identifying key areas for improvement in liquidity, solvency, and profitability. 

• Applied Principal Component Analysis (PCA) to streamline financial data, achieving a dimensionality reduction that explained 80% of variance and facilitated comparison with competitors. 

• Designed and implemented an automated Excel tool for financial index calculations, improving data processing efficiency by 35% and enhancing overall analytical productivity by 40%. 

• Provided strategic insights to enhance Paesano’s competitive positioning, with targeted recommendations to raise Return on Equity (ROE) by 2% over two years.

 Vucia Social Media Marketing Data Analyst October 2024

 • Analyzed Instagram and TikTok performance metrics over one year, identifying that Reels accounted for 97.4% of interactions and 93.8% of views on Instagram, and product comparison videos were the top-performers on TikTok with 622,743 views.

 • Conducted demographic analysis, revealing a strong follower base in Palermo on Instagram (26.5%) and 79.9% in Italy on TikTok, with an increasing international audience from France (3.9%) and Germany (0.5%). 

• Recommended strategic adjustments including increased Reels frequency, targeting non-local audiences, and optimizing TikTok posts at peak activity times (12:00) for higher engagement. 

• Developed data-driven content recommendations projected to increase total engagement by 30%, with specific strategies to boost female follower engagement (currently 22% on TikTok).

University of Palermo University of Palermo 

• Master’s in Statistics and Data Science, 2024 
• Bachelor’s in Economics and Finance