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Causal AI Consulting
Year
2025
Tech & Technique
Python, Numpy, Pandas, Scikit-learn, DoWhy
Description
A Causal AI Consultancy for Understanding and Minimizing Course Purchase Cancellations.
Key Features:
Key Features:
- 🧠 Causal AI Powered Analysis: Leverages Causal AI to deeply understand the root causes behind course purchase cancellations.
- 🔍 Key Driver Identification: Pinpoints the specific factors and events most influential in driving cancellations.
- 📉 Cancellation Minimization Strategies: Develops and recommends targeted interventions and strategies to effectively reduce churn rates.
- 📊 Actionable Insights: Provides clear, data-driven insights and recommendations for improving customer retention and course offerings.
- 📈 Predictive Modeling: Implements models to proactively identify customers at risk of cancelling their purchase.
My Role
Data Scientist
- 🤖 Machine Learning: Developed and implemented machine learning models to predict the probability of course purchase cancellations, enabling targeted interventions and risk assessment.
- 🧠 Causal Inference: Applied causal inference methodologies to identify the underlying causes of cancellations, isolate the impact of various factors, and recommend effective strategies to reduce churn based on causal evidence.
- 💡 Strategic Insights: Provided data-driven insights and recommendations to understand customer behavior patterns leading to cancellations and informed strategic decisions to minimize revenue loss.
- ✨ Feature Engineering: Designed, developed, and refined relevant features from raw data, significantly improving the predictive power of machine learning models and the accuracy of causal analyses.