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Your Name
PROFESSIONAL SUMMARY
Analytical and detail-oriented Data Professional with proven skills in exploratory data analysis (EDA), predictive machine learning modeling, and automated ETL data pipelines. Adept at translating complex datasets into actionable business intelligence using Python, SQL, and interactive dashboards.
TECHNICAL SKILLS
Languages: Python, SQL (PostgreSQL, MySQL), R, Statistics
Data Science & ML: Pandas, NumPy, Scikit-Learn, XGBoost, Machine Learning, Data Analysis
Data Engineering & ETL: DuckDB, Apache Airflow, ETL, REST APIs, JSON/Parquet
BI & Visualization: PowerBI, Tableau, Streamlit, Data Visualization, Excel (Advanced VLOOKUP & Pivots)
Tools: Jupyter Notebooks, Git, Docker, Google Colab
PROJECTS
Automated Customer Churn Prediction & Retention Analytics Engine
View ATS- Architected a machine learning customer churn classification model using XGBoost and Scikit-Learn, achieving an 89% ROC-AUC score across 250,000+ customer records.
- Engineered automated feature extraction pipelines covering RFM, session frequency, and velocity, isolating top 5 predictive factors for user attrition.
- Deployed a FastAPI real-time inference microservice processing churn risk scores in under 20ms, alerting account managers to prevent $120,000+ monthly ARR loss.
- Developed an executive PowerBI and Tableau dashboard with automated daily refreshes, improving data reporting turnaround times by 70%.
High-Volume E-Commerce ETL Pipeline & Sales Analytics Lake
View ATS- Engineered a daily automated ETL pipeline converting multi-source CSV and JSON sales feeds into partitioned Parquet data lakes, reducing query costs by 65%.
- Built an interactive Streamlit analytics application with cohort filters, identifying $85,000 in untracked inventory holding costs.
EDUCATION
Core Coursework:
