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Python NumPy Pandas Plotly Matplotlib scikit-learn SciPy MySQL MongoDB Postgres Power Bi Docker GitHub Git
Static Badge Static Badge Static Badge Static Badge Static Badge Static Badge Static Badge Static Badge
Python NumPy Pandas Plotly Matplotlib scikit-learn SciPy MySQL MongoDB Postgres Power Bi Docker GitHub Git
Leveraged survival analysis techniques (Kaplan-Meier, Cox model) to estimate customer lifetime and pinpoint periods of elevated churn risk.
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Analyzed behavioral and transactional indicators to uncover key churn drivers, developed predictive models to identify high-risk users and guide targeted retention strategies.
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Performed Recency, Frequency, and Monetary (RFM) analysis to classify customers into meaningful segments, supporting personalized marketing and retention strategies.
Jupyter Notebook 1
Applied association rule mining to retail transactions to discover frequently co-purchased items and uncover cross-selling opportunities.
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Conducted cohort-based analysis on acquisition data to reveal long-term retention patterns and lifecycle behavior across user groups.
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Analyzed the factors influencing house-buying behavior.
Jupyter Notebook