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Amy Zambrano

@amyzambrano

Message

Data analyst using Python and SQL to turn e-commerce data into profitability, conversion, and customer-value insights.

Ecuador

Message

Through independent e-commerce analytics projects, I’ve turned messy transactional and behavioral data into insights on profitability, conversion, delivery times, and customer satisfaction. I cleaned and joined datasets, analyzed the results, and translated findings into business recommendations.

For my e-commerce profitability analysis, I used Excel, Power Query, and SQL to calculate revenue, customer lifetime value, and conversion metrics, then presented them in an interactive Looker Studio dashboard. I also analyzed delivery times and customer satisfaction in Python, using visualizations to communicate logistics findings to non-technical audiences.

Experience

Work history, roles, and key accomplishments

E-commerce Logistics Analysis

Hands-on Data Analysis Projects

Designed a data cleaning and transformation pipeline in Python on a public dataset of over 100,000 e-commerce orders, integrating 6 relational tables through joins. Analyzed customer satisfaction by product category and created visualizations in Matplotlib to communicate findings.

Pandas Matplotlib Data Cleaning and Transformation Table Joins and Consolidation Dimensional Modeling Descriptive Analytics Logistics KPIs Customer Satisfaction Analysis Business Insights

E-commerce Profitability Analysis

Hands-on Data Analysis Projects

Cleaned, standardized, and validated two public transactional datasets in Excel, Power Query, and SQL. Joined and modeled relational data via primary/foreign keys, wrote SQL queries to calculate profitability and conversion metrics, and built an interactive Looker Studio dashboard.