Economist with hands-on experience in business operations and decision-making. I use analytical tools and structured thinking to understand business performance and support better strategic and operational decisions.
I help businesses understand what is really happening in their operations and what actions generate the most impact.
I combine business judgment, operational experience, and applied analysis to structure information and guide decisions.
Key focus areas:
- Business operations analysis
- Commercial performance indicators
- Process improvement through data insights
- Translating data into actionable decisions
- Managed and scaled small businesses for over 10 years, leading teams and operations with measurable impact.
- Designed operational and financial structures that improve efficiency and decision-making.
- Applied data analysis (Python, Excel, Power BI) as a support tool, not the main focus.
- Business Operations Analysis
- Commercial Performance Analysis
- Exploratory Data Analysis (EDA)
- Structuring information for decision-making
- Translating data into actionable business insights
Python (Pandas, NumPy, Matplotlib, Seaborn)
Power BI
Excel (Advanced)
https://github.com/pedrotamani/01-retail-sales-analysis
Analyzed retail sales data to uncover sales patterns, product performance, and operational insights that support better commercial decision-making.
https://github.com/pedrotamani/02-customer-churn-analysis
Explored customer churn data to identify key factors affecting retention and support business decisions aimed at reducing customer attrition.
https://github.com/pedrotamani/03-churn-prediction-model
Built a machine learning model to predict customer churn using historical data, helping businesses anticipate churn risk and guide retention strategies.
https://github.com/pedrotamani/04-online-purchase-analysis
Performed exploratory data analysis on an online purchase dataset to examine pricing patterns, product categories, payment methods, and seller ratings, generating visual insights to better understand transaction behavior.
https://github.com/pedrotamani/05-sales-performance-analysis
Exploratory analysis of retail sales data to identify revenue patterns, category performance, regional trends, and key drivers of profitability. The project focuses on translating sales data into business insights that support operational and commercial decisions.
- Economist – Experience managing business operations and teams
- Business Operations & Commercial Development – Real-world decision-making
- Certified training in Data Science and Analytics
- Applying data analysis to real business problems
- Improving business storytelling with data visualizations
- Building structured analytical frameworks for operational decisions
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