Currently an Extern @Breaking Games
I transform data into actionable insights through advanced analytics and BI solutions. Let's unlock your data's potential!
Dive into my portfolio showcasing innovative data solutions, machine learning models, and interactive dashboards.
·
Built an end-to-end supply chain risk analytics solution on a SQLite star-schema data model, engineering dual XGBoost classification models to flag at-risk shipments and suppliers. Applied SHAP explainability to surface the key drivers behind each risk prediction. Delivered a 5-page Power BI dashboard and published the complete project (code, models, dashboard) to GitHub and Power BI Service with a recruiter-facing README.
·
Engineered a 6-phase pipeline on 7,043 IBM Telco customers: raw data ingestion into SQLite, 9 SQL business queries, Python EDA with 3 custom features, XGBoost classification (AUC-ROC 0.843), 4-page Power BI dashboard, and live Streamlit deployment. Implemented SHAP explainability and threshold tuning, and deployed a real-time churn predictor on Streamlit Community Cloud.
I transform data into actionable insights through advanced analytics and BI solutions. Let's unlock your data's potential!
Detail-oriented Data Analyst and BI Developer with hands-on experience in Power BI, DAX, SQL, Python, and machine learning. Adept at building end-to-end data pipelines — from SQL analysis and ML modelling to live Streamlit deployment and executive dashboards. Seeking entry-level Data Analyst, BI Developer, or Business Analyst roles where I can contribute to data-driven decision-making and grow within a collaborative analytics environment.
Externships
SQL & Database Architecture Externship with Breaking Games
Breaking Games
Experience
Data Analyst Intern
NMD Infotech, Pune · 2025 – Present
Career Break – Civil Services Preparation
UPSC / MPSC · 2022 – 2025
Education
IIT Guwahati & AlmaBetter
Professional Certification in Data Science & AI Engineering · Class of 2025
Pune University
Bachelor of Engineering
Skills
Built an end-to-end supply chain risk analytics solution on a SQLite star-schema data model, engineering dual XGBoost classification models to flag at-risk shipments and suppliers. Applied SHAP explainability to surface the key drivers behind each risk prediction. Delivered a 5-page Power BI dashboard and published the complete project (code, models, dashboard) to GitHub and Power BI Service with a recruiter-facing README.
Built an end-to-end supply chain risk analytics solution on a SQLite star-schema data model, engineering dual XGBoost classification models to flag at-risk shipments and suppliers. Applied SHAP explainability to surface the key drivers behind each risk prediction. Delivered a 5-page Power BI dashboard and published the complete project (code, models, dashboard) to GitHub and Power BI Service with a recruiter-facing README.
Engineered a 6-phase pipeline on 7,043 IBM Telco customers: raw data ingestion into SQLite, 9 SQL business queries, Python EDA with 3 custom features, XGBoost classification (AUC-ROC 0.843), 4-page Power BI dashboard, and live Streamlit deployment. Implemented SHAP explainability and threshold tuning, and deployed a real-time churn predictor on Streamlit Community Cloud.
Engineered a 6-phase pipeline on 7,043 IBM Telco customers: raw data ingestion into SQLite, 9 SQL business queries, Python EDA with 3 custom features, XGBoost classification (AUC-ROC 0.843), 4-page Power BI dashboard, and live Streamlit deployment. Implemented SHAP explainability and threshold tuning, and deployed a real-time churn predictor on Streamlit Community Cloud.
6-page interactive Power BI dashboard analysing 43 Asian countries using World Bank WDI data (1990–2022) with star-schema data model and 29 DAX measures across GDP, HDI, trade balance, and energy KPIs.
6-page interactive Power BI dashboard analysing 43 Asian countries using World Bank WDI data (1990–2022) with star-schema data model and 29 DAX measures across GDP, HDI, trade balance, and energy KPIs.
Designed a comprehensive sales performance dashboard analysing 8,800+ CRM records tracking over $10M in closed revenue with dynamic pivot tables, KPI scorecards, and trend charts.
Designed a comprehensive sales performance dashboard analysing 8,800+ CRM records tracking over $10M in closed revenue with dynamic pivot tables, KPI scorecards, and trend charts.
Built an interactive dual-platform dashboard addressing 30+ business scenario questions; modelled data into fact/dimension tables, created DAX measures for pricing trends and host KPIs, and identified price-inelastic high-demand micro-markets.
Built an interactive dual-platform dashboard addressing 30+ business scenario questions; modelled data into fact/dimension tables, created DAX measures for pricing trends and host KPIs, and identified price-inelastic high-demand micro-markets.
3-page interactive dashboard exploring 15,000+ LEGO sets with KPI cards, dynamic detail panel, and Decomposition Tree for category-to-theme-to-set drill-down; implemented DAX measures and multi-level interactive filters.
3-page interactive dashboard exploring 15,000+ LEGO sets with KPI cards, dynamic detail panel, and Decomposition Tree for category-to-theme-to-set drill-down; implemented DAX measures and multi-level interactive filters.
Ensemble model (Random Forest, Gradient Boosting, XGBoost) forecasting daily sales across 1,115 stores, achieving Test R² of 0.915 and MAPE of 14.23%; automated pipeline reducing manual estimation by 80%, saving 4,000+ hours annually.
Ensemble model (Random Forest, Gradient Boosting, XGBoost) forecasting daily sales across 1,115 stores, achieving Test R² of 0.915 and MAPE of 14.23%; automated pipeline reducing manual estimation by 80%, saving 4,000+ hours annually.
Clustered 7,787+ Netflix titles using PCA for dimensionality reduction, implementing K-Means, Agglomerative Clustering, and DBSCAN; achieved a silhouette score of 0.621.
Clustered 7,787+ Netflix titles using PCA for dimensionality reduction, implementing K-Means, Agglomerative Clustering, and DBSCAN; achieved a silhouette score of 0.621.
Designed relational schema for 10 key e-commerce entities; wrote SQL queries for product performance, pricing trends, customer behaviour, and seller metrics; optimised retrieval via PostgreSQL indexing strategies.
Designed relational schema for 10 key e-commerce entities; wrote SQL queries for product performance, pricing trends, customer behaviour, and seller metrics; optimised retrieval via PostgreSQL indexing strategies.