Education
CGPA: 9.61/10.00
Major Subjects covered: Computer programming, Advanced Math, Economics
12th Grade Score: 94%
CBSE Subjects: Computer Science, Physics, Chemistry, Math, English
Work Experience
Working as a Software Developer in Siemens Energy
Built and deployed a full-stack Customer Insight Engine using React 19, Vite, FastAPI, and PostgreSQL on AWS (EC2, Lambda, S3, RDS), integrating OpenAI and Anthropic models for automated email analysis and optimized SharePoint data ingestion.
Developed and productionized 2 DOME applications for headcount tracking and NCC forecasting using Flask and PostgreSQL, eliminating 350+ hours/month of manual effort per application; deployed on AWS with EC2, S3, and Cron-based automation.
Enhanced Connect AI, an enterprise RAG chatbot built with OpenAI, LangChain multi-agent orchestration, and Azure AI Search, extending its multilingual engine with automated diagram and PowerPoint generation and complex RTL formatting.
Built a multi-agent LLM evaluation framework with conversational and sentiment-aware agents for automated regression testing, and architected a semantic query-complexity router that dynamically allocated LLM workloads, reducing inference costs by 10%.
Developed a real-time LLM workflow visualization layer that surfaces live agent progress and analysis stages to users.
Built 3 automated customer-facing Power BI dashboards integrating Oracle, Salesforce, and SharePoint Lists with authentication workflows, replacing manual report generation and improving customer meeting quality.
Built an integrated automated Power BI + Power Apps + Copilot Studio solution to replace manual updates, centralizing KPIs, reports, and outage Gantt timelines while enabling AI-assisted comment ingestion, reducing manual effort by 70%.
Built 2 AI-powered feedback analytics dashboards with automated NLP pipelines for sentiment, thematic analysis, Bradley Curve maturity, risk assessment, mental-health indicators, and actionable recommendations.
Analyzed and optimized an XGBoost-based seat factor prediction model, identifying key areas for improvement.
Built a modular intraday NIFTY options research framework with dynamic Greeks neutralization.
Automated processing of 300K+ bulk-deal records and joined them with BHAV price history in DuckDB to generate indicators
Worked as Revenue Optimization - Operations Research intern at Emirates Airlines
Analyzed and optimized an XGBoost-based seat factor prediction model, identifying key areas for improvement.
Engineered new features (OD Flight Connectivity, Closure %, Seat Factor Percentage), boosting prediction accuracy by 5-7%.
Developed three interactive Dash applications to visualize flight booking patterns and sales trends.
Enabled data-driven decision-making through actionable insights derived from predictive modeling and analytics.
Worked at Rituals, a luxury well-being brand under Apparel group.
Focused on creating dashboards for better analysis of e-commerce performance.
Created dashboards using power bi and intermediate analysis with excel.
Understood basics of a working business with in-depth knowledge of sales and stock management.