🎓 BSc Physical Science (Computers Science)
📊 Actively learning and building projects in Data Science & Machine Learning

• 🔭 Working on real-world ML & analytics problems
• 📈 Interested in Forecasting, Segmentation, Churn, CLV, Lead Scoring & Risk Modeling
• 🧠 Focus on understanding why a model works, not just results
• 🎯 Long-term goal: Professional Data Scientist/AI Engineer

• Pandas, NumPy, Scikit-Learn, Tensorflow, Statsmodel
• Matplotlib, Seaborn
• Exploratory Data Analysis, Feature Engineering & Model Evaluation
• Advanced Excel, Power BI (Dashboards & KPIs)
• MySQL, PostgreSQL

• Built churn prediction models using transactional data
• Identified high-value customers at risk of silent attrition
• Combined CLV + churn probability for better business decisions

• Developed ML-based lead scoring model
• Evaluated performance beyond default accuracy
• Used precision-recall analysis & cutoff optimization
• Translated probabilities into actionable sales categories

• Integrated traffic, weather & event datasets
• Performed time-based analysis for demand patterns
• Generated operational insights

“Data is useful only when it leads to better decisions.”