Data Analyst with hands-on experience in operations analytics, quality intelligence, process reporting, dashboard automation, and applied AI tools for business decision support. Final-year BCA (Machine Learning) student.
Radical Minds Technologies Pvt. Ltd.
Feb 2026 – Present · Gurugram
Analyze case-taking trends across the Philips after-sales process; perform model-wise issue analysis and root cause identification; conduct quality audits and audit mapping; built an AI-assisted chatbot integrating process SOPs; engineered an automated NPS tracking dashboard that produces a downloadable Excel report; designed Excel, Power BI, and Python tools to automate recurring reporting.
NIRDC (IND AAP)
Oct 2025 – Feb 2026 · Gurugram
Collected, cleaned, and analyzed operational and performance data; built dashboards and analytical reports for senior management; coordinated with cross-functional teams to ensure data accuracy and timely reporting; supported R&D initiatives through documentation, reporting, and insight generation.
Settlemed.ai
Sep 2025 – Oct 2025
Validated and maintained healthcare datasets for accuracy and data integrity; supported reporting and analytics workflows for automation and process optimization initiatives.
Microsoft
Jul 2024 – Sep 2024
Built AI and data analysis workflows using Microsoft Azure services; performed exploratory data analysis and created interactive Power BI dashboards for insight presentation.
Bachelor of Computer Applications (BCA), Machine Learning
2023 – Present
Intermediate (12th)
2021
Matriculation (10th)
2018
Built an end-to-end machine learning pipeline using Logistic Regression and Random Forest to predict customer churn, achieving over 85% accuracy. Performed feature engineering and exploratory data analysis to improve model performance and generate retention-focused insights. Stack: Python, Pandas, Scikit-learn, Matplotlib.
Built an ARIMA-based forecasting model to predict monthly sales trends and support inventory planning. Analyzed seasonality and trend components and visualized actual versus forecasted sales to validate model accuracy. Stack: Python, Pandas, Statsmodels, Matplotlib.
Built a symptom-based disease prediction system using Naive Bayes and Decision Tree models for early-stage screening. Handled data preprocessing and label encoding and built a simple interface for user-input testing. Stack: Python, Pandas, Scikit-learn.