Client / Context:
A retail chain with national operations and a large customer base but underutilized data systems.

Problem:
Although they had vast amounts of transactional data, they lacked the tools to extract meaningful insights or predict customer behavior.

Solution:
I architected a modern analytics platform using GCP tools (BigQuery, Dataflow, Cloud Functions). I trained ML models to segment users and predict churn using Python, and built dynamic dashboards with Looker to empower marketing and business teams.

Impact / Results:

• 25% increase in marketing campaign ROI

• 12% boost in customer retention

• Enabled data-driven decision-making across departments

Tech Stack: GCP (BigQuery, Dataflow), Python, scikit-learn, Looker, Cloud Functions

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