Leading the data analytics function — from data pipelines to decision-ready models and reporting.

• Designed and maintained ETL pipelines in Python (pandas) and SQL — extracting from production MySQL, transforming multi-table operational data into clean, analytics-ready models, and loading them into datasets, dashboards, and reports.
• Modeled operational data with complex MySQL transformations (multi-table joins, CASE logic, time-difference staging) to represent the order-fulfillment lifecycle across vendor, QC, purchase, and shelving stages.
• Built revenue forecasting models (flat run-rate, actuals + run-rate, and day-of-week–weighted projections) to predict monthly placed and realized revenue for leadership.
• Developed cancellation and funnel analytics — quantifying cancellation rate by count and value, modeling recovery scenarios, and estimating revenue uplift from improvements.
• Owned the semantic layer between raw data and business teams — turning operational tables into trusted metrics and self-serve datasets.

• Python
• pandas
• SQL
• MySQL
• Power BI
• Statistical Data Analysis

Led analysis and reporting across product, growth, and operations.

• Performed business data analysis to uncover actionable insights and support strategic decision-making.
• Analyzed customer behavior, purchasing patterns, and business trends to identify growth opportunities.
• Collected, cleaned, and analyzed large, complex datasets to identify meaningful trends, patterns, and performance indicators.
• Monitored business growth and prepared analytical reports and presentations for stakeholders and management.
• Designed and maintained interactive dashboards and KPI reports to enable real-time, data-driven decision-making.
• Collaborated with cross-functional teams to improve reporting processes and optimize business performance.

• SQL
• MySQL
• Python
• Power BI

Turned operational and customer data into actionable business insight.

• Performed business data analysis to uncover actionable insights and support strategic decision-making.
• Analyzed customer behavior, purchasing patterns, and business trends to identify growth opportunities.

• MySQL
• Microsoft Power BI
• SQL
• Excel
• Data Analysis

Drove business development while using data analysis to inform decisions.

• Data Analysis
• Business Development

Gained foundational knowledge across several business and technical areas.