I am a data analyst with an engineering and B2B product marketing background.
My past professional and educational experience in multinational companies shapes how I frame questions, interpret results, and communicate actionable insights to non-technical stakeholders.
I focus on extracting practical value from real-world data using Python, SQL, and Power BI.
Primary focus:
- ETL
- Data analysis with Python (pandas, numpy, matplotlib) and SQL (PostgreSQL & T-SQL)
- Business analysis and visualization with Excel and Power BI
- Structured problem-solving applied to real-world datasets
Supporting tools and environments:
- SQL (foundations & data handling; Microsoft SQL Server)
- Swift & Xcode (iOS prototyping), Visual Studio (Python scripting)
- GitHub, Jira
- macOS, Linux, Windows
Goal: Evaluate real-world fuel consumption data to determine whether hybrid ownership delivers measurable cost savings and to identify the most efficient commuting route.
Key insight: Hybrid usage reduced fuel costs by approximately 15% on average, with consistent savings across different commuting routes.
Tools: Excel, Power BI
Explore:
- Power BI Desktop file
- Sample visualization:
Goal:
Build a proof-of-concept analytics pipeline to visualize multi-store sales performance and customer buying behavior while ensuring PII is removed at ingestion and never exposed in BI tools.
What I focused on:
Privacy-by-design ETL, analytical reasoning (fixed markup → profit ≈ revenue), scalable pipeline design, and effective dashboards.
Tools:
Python (ingestion, parsing, anonymization), Power BI (visualization)
Explore:
- Python data ingestion & anonymization pipeline:
👉 Privacy-First Sales Analytics Pilot (Car Dealership) (Python) - Power BI dashboard (local pilot):
👉 Privacy-First Sales Analytics Pilot (Car Dealership) (Power BI)
Swift-based prototype for estimating EV charging costs and comparing efficiency metrics using user-input and consumption data.
- Engineering-led data analysis focused on efficiency, cost, and performance trade-offs
- Product-oriented mindset: framing analytical questions around decisions, not just metrics
- Strong experience working with longitudinal, real-world datasets
- Clear communication of insights for non-technical stakeholders
I am open to data analyst and analytics roles, particularly where technology and business insight intersect.
© 2026 Paolo Vasta. All rights reserved.
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No reuse, modification, or redistribution of any part of this repository is permitted without explicit written permission from the author.