Developer
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Built an XGBoost-based delivery ETA prediction system using Python and Scikit-learn on historical shipment data, identifying high-risk deliveries across multiple pincodes and reducing the late delivery rate from 19% to 10% through proactive operational interventions. Designed an XGBoost-based customer propensity model using historical purchase behavior to identify pet parent customers likely to purchase from additional supercategories, enabling personalized cross-category recommendations and improving customer engagement. Developed a Python-based backend pipeline to summarize customer support tickets and agent conversations using LLMs, generating concise, context-aware summaries that enabled faster issue resolution and reduced manual review effort for support teams.
Software Development Engineer (Internship) at Flipkart (2026-01 – 2026-07)
Bachelor of Technology in Information Technology – Indian Institute Of Information Technology, Lucknow (IIITL) (2022-11 – 2026-06)
Intermediate (12th Grade) – Sri Chaitanya College (2020-11 – 2022-07)
Secondary Education (10th Grade) – Sri Chaitanya Techno School (2019-07 – 2020-04)