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Harsh Shah
Intern-level product and data analyst specializing in analytics and automation
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Analytics candidate who has built full-stack data products end to end: from cleaning 1M+ retail transactions in MySQL to Python-based market basket analysis, churn segmentation, and Streamlit dashboards with Gemini-powered business recommendations. Also built a reproducible predictive modeling workflow for concrete strength forecasting, showing a blend of SQL, machine learning, and stakeholder-friendly delivery.
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Key Strengths
- Built end-to-end analytics pipelines from raw data to stakeholder-facing dashboards
- Strong SQL data cleaning and transformation on 1M+ retail transactions
- Thoughtful handling of messy data and edge cases instead of dropping records blindly
- Validated outputs with row-count checks and revenue reconciliations against raw data
- Improved query performance with indexing on key filter columns
- Integrated SQL outputs with Python for scalable market basket analysis
- Optimized large basket matrices by filtering high-frequency SKUs and using memory-efficient boolean types
- Structured Python workflows into modular, reproducible functions with fixed random seeds
- Applied customer segmentation, churn-risk logic, and cohort analysis to retail use cases
- Translated analytics into plain-language recommendations via Streamlit and Gemini
- Built a real-time concrete strength prediction tool for engineering users
- Strong focus on stakeholder usability and actionability of metrics
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