Professional Summary
Pre-final year B.Tech CSE student specializing in Data Analytics and Business Intelligence. Experienced in data preparation, SQL querying, ETL routines, and building interactive visualization dashboards. Proficient in Python, SQL, Pandas, Seaborn, and Streamlit, with a history of launching 10+ live analytical web applications. Passionate about parsing messy transactional records to extract actionable customer retention metrics and business KPIs.
Education
B.Tech in Computer Science & Engineering (Specialization: Cloud Computing & Machine Learning)
- Academic Standings: CGPA: 8.0+ / 10. Relevant Coursework: Database Management (DBMS), SQL Data Structuring, Applied Data Analytics, Systems Logic, Cloud Infrastructure, Python.
Technical Skills
Analytics & Visuals:
Exploratory Data Analysis (EDA), Cohort Segmentation, Trend & Churn Metrics, Seaborn, Matplotlib
Data Preparation & SQL:
SQL Queries (Data Wrangling, Joins, Aggregations), ETL Pipelines, Pandas, NumPy, Schema Formatting
Dashboards & Hosting:
Streamlit Interactive Interfaces, Git, GitHub Actions, Vercel, Render, Spreadsheet Modeling
Core Tech:
Python, SQL, C
Projects
Python, Pandas, Seaborn, Customer Cohorts, Streamlit, Business KPIs
- Cleaned, prepared, and formatted 10,000+ credit records, sorting null indices and mapping categorical fields.
- Conducted deep cohort analysis using Pandas, isolating churn triggers linked to card inactivity and contact frequencies.
- Developed an interactive Streamlit dashboard visualizing customer attrition curves, providing immediate recommendations for retention.
Python, Streamlit, Data Visualization, Vercel, Interface Design
- Created a customer-facing pricing calculator using Streamlit, configuring slider metrics and value grids.
- Visualized property valuation sensitivity charts, enabling non-technical users to observe feature interactions.
- Managed code deployment to Vercel, ensuring high availability and seamless frontend query latency.
Experience & Open Source Contributions
- Published verified dataset descriptions and visualization dashboards on Kaggle, verifying cleaning and analysis steps.
- Maintained 10+ public GitHub repositories featuring clean data analysis pipelines, SQL scripts, and documentation.
- Collaborated on competitive code challenges in Coderush 2.0 (2025), utilizing Pandas for quick dataset indexing and optimization.