About
Data Analyst skilled in SQL, Python, Excel, and Power BI, built through hands-on projects covering data extraction, cleaning, EDA, and visualization. Built and analyzed datasets of 8K+ records to uncover revenue trends, retention patterns, and actionable business insights. Proficient in building interactive dashboards, KPI reporting, and BI solutions, with practical exposure to Machine Learning and Generative AI integration for AI-powered analytics applications.
Skills & Expertise (34)
Work Experience
Project Lead
AI-Powered Customer Churn Prediction & Retention Intelligence System
Present - Present
Built end-to-end AI-powered churn prediction system analyzing 594 customers and 3,000 transactions using SQL, Python, Excel, and Power BI, delivering actionable retention insights across 12 months of data. Engineered 7 ML features using RFM Analysis and trained Logistic Regression and Random Forest classifiers achieving 85%+ accuracy and 0.90 AUC score; integrated Groq LLM API to generate AI-powered churn risk explanations and business reports for non-technical stakeholders. Designed 4-page interactive Power BI dashboard with 15+ visualizations — KPI cards, churn heatmaps, RFM scatter plots and region-wise trends — improving business intelligence reporting. Deployed live Streamlit web application with real-time churn prediction, AI chatbot, interactive analytics and downloadable reports.
Project Lead
Global E-Commerce Sales & Customer Intelligence Analysis
Present - Present
Analyzed 8K+ transactions generating 10.23M revenue and 2.31M profit using SQL (CTEs, aggregations). Identified regional performance trends, with West leading (2.64M) and balanced revenue distribution across regions. Detected impact of 15% average discount on profit margins and category-wise performance (Furniture highest at 2.7M). Built Power BI dashboard showcasing KPIs, sales trends, and mid-year revenue decline patterns.
Project Lead
Spotify Streaming Intelligence & Popularity Analysis
Present - Present
Analyzed 5,000 songs generating 5B streams to evaluate streaming patterns and user behavior. Identified top-performing countries, with Brazil and Canada contributing 530M streams each. Observed 56% users on premium subscriptions, indicating higher paid user contribution. Built Power BI dashboard analyzing genre distribution, song popularity trends, and streaming patterns.
Education
Master of Computer Applications (MCA) - The National Institute of Engineering
2023 - 2025 · Afghanistan
Bachelor of Computer Applications (BCA) - Seshadripuram Degree College
2020 - 2023 · Afghanistan
Certifications
Complete Data Analyst Bootcamp From Basics to Advanced
Udemy · 2026
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Skills (34)
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