Analyzing and determining Stripe's 2026 Summer merchant list for targeted marketing.
Summer 2026 Assignment
This repository contains the strategic analysis and metric calculations developed for the Stripe Data Analyst Co-op take-home assessment. The project focuses on deriving actionable business insights from transactional and merchant datasets.
🔒 Data & Code Confidentiality Notice: > To comply with strict data privacy standards and the proprietary nature of this assessment, the original datasets, programmatic pipelines, and source code (
.ipynb) have been withheld from this public repository. The files provided here focus exclusively on the final business logic and strategic deliverables.
The goal of this analysis was to move beyond simple data aggregation and provide a cohesive narrative regarding merchant performance and transaction health.
- Strategic Reporting: Synthesized complex programmatic outputs into a clear, executive-facing report designed for cross-functional stakeholders.
- Metric Definition: Rigorously defined and calculated core business metrics to evaluate platform health and user behavior.
While the source code is withheld, the analysis was conducted using the following technical architecture:
- Data Processing Pipeline: Utilized
Python (Pandas, NumPy)to ingest, clean, and join multi-table schemas. Handled categorical encoding and datetime manipulations for time-series aggregation. - Metric Calculation: Formulated precise logic to extract metrics like processing volume and conversion rates from raw event logs. (in progress)