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Nav1022/README.md

Hi, I'm Manav Patel

Data Analyst | Aspiring Data Scientist

Turning raw business data into decisions through ML, statistical modeling, and BI dashboards.

📍 Jaipur, India · 📧 manav99ps@gmail.com · 🔗 LinkedIn

Skills

Languages/DB: Python, SQL, MySQL ML: Scikit-learn, XGBoost, Statsmodels, TensorFlow, SHAP, Time Series Forecasting BI: Power BI, Tableau, Excel Tools: Streamlit, Git/GitHub

Projects

Loan Default Risk Prediction — Python XGBoost SHAP Streamlit Credit risk classifier (LogReg/RF/XGBoost) with threshold tuning + SHAP explainability. 0.80 ROC-AUC, catches 71% of defaults.

Retail Demand Forecasting — Python Statsmodels Benchmarked 4 forecasting methods on 8+ years of sales data. Holt-Winters cut error 33% vs. baseline.

Customer Churn Prediction — Python SQL Tableau Churn model + dashboards. 15% accuracy gain, supported a 10% churn reduction.

Sales Performance Dashboard — Power BI SQL KPI dashboard across 6 categories/4 regions. Surfaced top 10 products driving ~59% of revenue.

📫 manav99ps@gmail.com · LinkedIn

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  1. customer-churn-prediction customer-churn-prediction Public

    End-to-end customer churn prediction system: combines data from 4 sources with SQL, trains and compares ML models (Logistic Regression, Random Forest, Gradient Boosting), and exports churn-risk sco…

  2. retail-data-analysis-excel retail-data-analysis-excel Public

    Excel retail analytics dashboard built with VLOOKUP, SUMIF summaries, and charts — turns 5,000 transactions into KPI cards and category/monthly insights.

    Python

  3. sales-performance-dashboard sales-performance-dashboard Public

    End-to-end sales analytics: 5 relational tables joined with SQL into KPI marts, feeding a Power BI dashboard tracking revenue, product, and regional performance over 24 months.

  4. loan-default-risk loan-default-risk Public

    ML pipeline predicting loan default risk (UCI German Credit dataset, 1,000 applicants). Compares Logistic Regression, Random Forest & XGBoost with 5-fold CV, tunes the decision threshold via precis…

    Python

  5. retail-demand-forecast retail-demand-forecast Public

    Benchmarks 4 forecasting methods (Seasonal Naive, Holt-Winters, SARIMA, feature-engineered Random Forest) on 8+ years of monthly retail sales, validated on a strict 12-month holdout. Holt-Winters w…

    Python