Hi, I'm Pietro Gazzi
Technical Solutions & Analytics Engineer | Python | SQL | Data Governance | Process Automation
Technical Solutions & Analytics Engineer | Python | SQL | Data Governance | Process Automation
Educational Background: I hold a Bachelor's Degree in Mechanical Engineering and a Master's Degree in Industrial Engineering, which have provided me with a solid foundation in problem-solving and analytical thinking. Over the years, I have further refined my expertise through certifications in Data Science, Machine Learning, and Finance, all of which have enabled me to transition into the world of Technical Solutions and Analytics Engineering.
Continuous Learning: I am committed to staying ahead of industry trends, constantly learning new tools and methodologies to improve my analysis. Whether it is through following industry blogs, attending webinars, or taking new certifications, I ensure my skills remain sharp and relevant to the ever-evolving data landscape.
Motivation: My journey was fueled by a strong curiosity and a desire to solve complex technical challenges. With a deep interest in process automation, data architecture, and innovation, I am passionate about building systems that drive meaningful change and improve business operations. Ultimately, what drives me is the opportunity to replace inefficiencies with scalable, automated tech solutions that make a tangible impact.
Core Skills: I have developed a diverse skill set, including Python, SQL, PostgreSQL, and modern BI tools. I have experience working in advanced technical environments such as Thales Alenia Space and Leonardo Helicopters. In my current role at Leonardo, I spearhead Data Governance and Performance Monitoring initiatives. By developing custom Python and SQL solutions, I have automated complex reporting and optimized department-wide processes, significantly improving data accuracy and operational efficiency.
Soft Skills: I combine my technical skills with a logical, problem-solving mindset. I thrive on breaking down complex, failing processes and engineering robust, user-friendly solutions.
Personal Interests: Running and spending time in the mountains are my ways of taking on new challenges. They require dedication and persistence, qualities I value. I'm also a devoted Fiorentina supporter and never miss a match.
Explore some of the key projects I have worked on. Click the project titles to view the details and access the GitHub repositories for each project.
Description: A robust desktop application built with Python and Tkinter that successfully replaced an underperforming external software. I developed this in-house tool from the ground up to manage and streamline complex workflows, resulting in optimized office operations, enhanced data accuracy, and a significant reduction in processing time.
Description: A fully integrated CRM system built using PostgreSQL, Python, and Power BI. The system manages customer data, tracks sales opportunities, and monitors interactions, providing valuable insights for improving customer relationships and business strategies.
Description: This project focuses on analyzing Walmart store sales and forecasting future sales using machine learning techniques. Using the "Walmart Recruiting - Store Sales Forecasting" dataset available on Kaggle, I explore sales trends, identify key factors influencing sales, and build predictive models to improve business decision-making.
Description: This project analyzes customer purchasing behavior using the Online Retail Dataset (UCI Machine Learning). We implement RFM analysis (Recency, Frequency, Monetary) and use K-Means clustering to segment customers. The results are displayed in an interactive Streamlit dashboard.
Description: This project focuses on optimizing investment portfolios using Modern Portfolio Theory (MPT). The goal is to build a web-based tool that allows users to input stock tickers and receive an optimized portfolio allocation. The model calculates the Efficient Frontier, Minimum Variance Portfolio (MVP), and Maximum Sharpe Ratio Portfolio (MSR) to help investors balance risk and return effectively.
Description: A responsive portfolio website for an artist, built with HTML, CSS, and JavaScript. It showcases the artist's work in a clean and modern design, and it's easy to navigate.
Below are some of the exercises I completed for various certifications, each project showcasing specific skills and knowledge developed using R and python:
Description: Optimizing investment portfolios using the Efficient Frontier, Minimum Variance Portfolio (MVP), and Maximum Sharpe Ratio Portfolio (MSR) to balance risk and return for informed decision-making.
Description: Developed an interactive web application to demonstrate hypothesis testing concepts using R. Utilized Shiny and ggplot2 to create dynamic visualizations that enhance user understanding of statistical methods.
Description: Conducted a linear regression analysis using R and RStudio. Analyzed a real-world dataset to identify trends and make predictions, highlighting the practical application of statistical modeling techniques.
Description: Created a machine learning model using R to classify workout types based on sensor data. Implemented a Random Forest algorithm with cross-validation to achieve high accuracy in predictions.
Description: Developed a predictive model in R to identify a user's native language based on their text input. Utilized natural language processing (NLP) techniques and libraries such as tm and caret to build and evaluate the model.