Vibe Coding
Business Intelligence
AI Automation
Scroll
What I do
From understanding business requirements and exploring raw data to delivering clear insights, I manage the complete analytics process end-to-end.
Data Analysis & Machine Learning
I clean, process, and analyze data, then build and train machine learning models to uncover patterns and predict outcomes that support smarter business decisions.
Dashboard & Data Visualization
I create interactive dashboards and visual reports that transform complex data and model outputs into clear, easy-to-understand stories.
Business Intelligence & Reporting
I develop structured reports and performance metrics grounded in data and AI-driven insights, tracking performance and supporting strategic growth.
ProblemDEFINE
Data MiningEXTRACT
Data CleaningFILTER
Feature EngineeringRESHAPE
ExplorationDISCOVER
VisualizationCHART
Model TrainingTRAIN
Hyperparameter TuningTUNE
EvaluationMEASURE
PredictionFORECAST
InsightsREVEAL
PresentationCOMMUNICATE
DecisionACT
ProblemDEFINE
Data MiningEXTRACT
Data CleaningFILTER
Feature EngineeringRESHAPE
ExplorationDISCOVER
VisualizationCHART
Model TrainingTRAIN
Hyperparameter TuningTUNE
EvaluationMEASURE
PredictionFORECAST
InsightsREVEAL
PresentationCOMMUNICATE
DecisionACT
Skills
Excel
Data Analysis & Automation
88%
Power BI
Dashboard & Visualization
92%
SQL
Data Querying & Management
82%
Python
Data Analysis, AI & Machine Learning
80%
WordPress
Website Development
75%
Education
2027
MBA
Business Analytics and Data Science
Vidyasagar University
Focused on business intelligence, data analytics, and data-driven decision-making.
2022
M.Sc.
Applied Mathematics
University of Kalyani
Built a strong foundation in statistical analysis, mathematical modeling, and analytical problem-solving.
Projects:
Supply Chain · Power BI
FMCG Supply Chain Management Analysis:
- Experienced inefficiencies in inventory management, demand forecasting, and supplier distribution across multiple warehouse locations.
- Identified regional demand gaps, supplier contribution imbalance, lead time variations, and mismatches between inventory and reorder levels.
- Developed an interactive Power BI dashboard to optimize inventory planning, improve demand forecasting, and support efficient supply chain decision-making.
Power BI
Excel
Power Query
EDA
View Insights
Real Estate · Python
Gurgaon Real Estate Market Analysis:
- Faced difficulty in identifying pricing patterns, premium locations, and investment opportunities due to unstructured and inconsistent property data.
- Identified high-value localities, pricing impact of RERA approval and property status, builder-driven price differences, and weak correlation between area and price per sqft.
- Performed end-to-end EDA using Pandas, Seaborn, and Matplotlib to clean data, analyze trends, and generate actionable insights for real estate decision-making.
Python
Pandas
Seaborn
Matplotlib
EDA
View Project
Forecasting · Python
E-Commerce Marketplace Demand Forecasting Study:
- Faced challenges in understanding demand patterns, forecasting accuracy, and seasonal variability across multiple product categories in e-commerce sales data.
- Identified high predictability in grocery demand (~80% accuracy), high volatility and forecasting error in electronics, and increased sales variability during festive periods.
- Applied a 30-day moving average forecasting model and built visualizations to evaluate MAPE, uncover seasonal trends, and support data-driven inventory and supply planning.
Python
Excel
Matplotlib
Seaborn
EDA
View Report
IPL Prediction · Supervised ML
IPL Match Win Prediction System:
- Faced challenges in predicting match outcomes using complex ball-by-ball data, requiring effective feature engineering and handling of real-time match scenarios.
- Identified that chasing teams had higher win probability (55.1%), logistic regression achieved the best performance (AUC: 0.760), and feature engineering had greater impact than complex models.
- Built an end-to-end ML pipeline with EDA, feature engineering, multiple model comparison, and a real-time prediction system to estimate match outcomes based on first innings performance and contextual factors.
Pandas
NumPy
Scikit-learn
Matplotlib
Seaborn
View Project
Customer Segmentation · BI & AI Dashboard
Clickstream Behavioral Analysis:
- Faced challenges in understanding user behavior, identifying high-intent customers, and reducing revenue loss due to cart abandonment and churn risk across the platform.
- Identified key segments like buyers, browsers, and researchers, along with critical insights such as 63.1% cart abandonment, high CLV churn exposure, and strong impact of session depth and timing on revenue.
- Developed an interactive AI Powered dashboard integrated with Excel-based analysis and AI-driven insights to enable user segmentation, revenue optimization, churn prevention, and targeted marketing strategies.
Power BI
Excel
Power Query
AI Dashboard
EDA
View Dashboard
Healthcare · Deep Learning Model
Breast Cancer Detection Neural Network:
- Faced challenges in accurately classifying tumors as benign or malignant using medical diagnostic data while avoiding overfitting and ensuring reliable model generalization.
- Identified strong class separation with high predictive performance (ROC-AUC: 0.9934, Accuracy: 98.25%) and minimal false negatives, highlighting the effectiveness of proper regularization and validation techniques.
- Built a deep neural network with batch normalization, dropout, L2 regularization, and stratified cross-validation to deliver a robust and reliable cancer detection system.
Python
TensorFlow
Scikit-learn
Matplotlib
View Project