🔹Successfully managed and coached underperforming employees, improving team performance and productivity.

🔹Participated in annual evaluations as a Bias Disruptor to ensure fair, unbiased assessments.

🔹Evaluated engineering contributions and presented results to leadership, securing recognition and career growth for team members.

🔹Integrated FC, Supply Chain, and Last Mile telemetry—scan events, GPS, lane latency, labor throughput, and SLA signals—into an ML anomaly detection pipeline using outlier models, isolation forests, and sequence embeddings, reducing NOC investigation cycles by 45% and defect triage by 30%.

🔹Engineered a predictive optimization framework using time-series forecasting, network flow models, and generative-AI simulators to assess surge volume, capacity constraints, and disruptions, cutting planning latency by 50% and stockout escalations by 32%.

🔹Developed a multimodal AI operations assistant using transformer models, graph embeddings, and NLP extraction of driver/associate notes, reducing triage load by 40%, improving ETA accuracy by 25%, and stabilizing cross-node reliability.

🔹Transformed an AWS QuickSight catalog into a RAG-based LLM conversational data catalog, increasing team efficiency by 60%.

🔹Engineered enhanced search across 780+ datasets by integrating metadata, lineage, feature engineering, and wiki content, boosting engagement by 40%.

🔹Built an Automated Metadata Generation System with Claude LLM and active learning, achieving 99% accuracy.

🔹Reduced manual curation by 500 hours/month through automated classification, PII tagging, and human-in-the-loop verification.

🔹Ensured GDPR and HIPAA compliance via AWS KMS encryption and a real-time logging/auditing system.

🔹Spearheaded the Research Data Lake (RDL) Catalog, saving $1.2M annually by reducing data duplication and improving discovery.

🔹Led a comprehensive Native AWS Migration, transitioning to a microservices architecture with serverless computing via AWS Lambda and containerization with Amazon ECS and EKS, resulting in a 30% reduction in operational costs and enhanced scalability across multiple international sites.

🔹Developed the ISRO One-Touch BI dashboard, featuring real-time data integration with AWS Kinesis and customizable KPI widgets, achieving a 40% reduction in decision-making time and supporting critical organizational objectives such as inventory optimization and cost management.

🔹Created a Configuration Work Station with an intuitive UI and built-in validation rules, automating data input and real-time simulations, which resulted in a 50% reduction in manual errors during transportation network configuration.

🔹Built the Suraksha mobile and web application with a scalable architecture using AWS ECS and Auto Scaling, successfully managing over 107,000 COVID-19 vaccination bookings while ensuring a seamless user experience through robust data encryption and intuitive UI/UX design.

🔹Cultivated team growth by promoting 6 team members and hiring 20 engineers, contributing to an $8.8 million reduction in costs and a $34.5 million uplift in revenue through effective leadership and strategic talent acquisition.

🔹Engineered Project Infinity real-time data pipeline using Apache Kafka, Apache Flink, and Amazon Kinesis, achieving a 70% reduction in processing latency through optimized data partitioning and in-memory caching, which enhanced live operational analytics.

🔹Developed the HEIMDALL ML-based tool for truck prioritization, integrating real-time data (GPS, traffic, inventory) and optimizing a custom ML model, resulting in a significant reduction in turn-around time from 6.7 to 2.2 hours, improving vendor experience.

🔹Implemented the Location Fraud Automation Tool (LoFAT) for Amazon Foods, targeting GPS spoofing and fake deliveries, saving $0.6 million and eliminating the need for 37 headcount hires through automated anomaly detection and real-time tracking.

🔹Created a Reactive Scheduling ML model incorporating demand forecasting and resource optimization, achieving $800,000 in annual savings in transportation scheduling through enhanced real-time rescheduling capabilities.

🔹Expanded the team from 3 to 8 members, overcoming challenges through pair programming and comprehensive onboarding, while implementing 9 serverless products that garnered 5 million views.

🔹Automated processes by creating 42 solutions that replaced manual tasks such as data entry and report generation, utilizing RPA and custom scripts, resulting in over 30,000 man-hours saved annually.

🔹Developed a web-based R-Shiny scheduling tool, replacing an Excel-based system and addressing inefficiencies such as manual data entry errors and lack of real-time updates, resulting in a 60% improvement in scheduling efficiency and an 80% reduction in scheduling-related errors.

🔹Maintained a 94% average productivity in the Inbound Frontline team through the implementation of a tiered support system, a comprehensive knowledge base, and regular training sessions, achieving performance 15% above the Amazon average and 10% higher than the previous year.

🔹Transitioned to the IPEX team, delivering high-impact projects for Supply Chain Operations, including an automated inventory reconciliation system that reduced discrepancies by 40%, a predictive maintenance system that cut equipment downtime by 30%, and a dynamic load balancing system that improved dock utilization by 25%.