Quality Analyst - Amazon - Bangalore, India
(2019-07)
- Led end-to-end redesign of the resignation workflow, analyzing 500+ contacts to identify transfer bottlenecks and advisor constraints. Built a thorough understanding of the process by reviewing contact recordings, identifying failure patterns, and mapping the full advisor journey. Proposed multiple solutions to relevant stakeholders, one of which was adopted, resulting in reduced transfers, improved First Contact Resolution (FCR), and an estimated $500K in annual cost savings.
- Designed, built, and launched a browser-based AI-powered tool that converts chat and call transcripts into structured, professional case notes. Reduced documentation time from approximately 3 minutes per case to approximately 30 seconds, a 90 percent reduction. Tool was leadership-endorsed, piloted across the team, and adopted by approximately 70 Quality Analysts with 2,000+ uses and approximately 700 views. Estimated annual savings of approximately $500K. Built entirely on a self-initiated basi
- Built an AI-powered application that fully automates the abusive contact investigation process, cutting investigation time from 45 to 60 minutes down to approximately 10 minutes, an 80 percent reduction. The app automates evidence gathering, contact pattern identification, and case documentation from start to finish. Delivered live demonstrations to QAs and leadership to showcase reliability and build confidence in AI-assisted investigations. Continued refinements are underway to improve accurac
- Built an automated follow-up tracking system that manages the structured 5-day escalation process for abusive contact investigations. The tracker ensures timely follow-ups at each escalation level across the five-day workflow, eliminating missed follow-ups and ensuring compliance with escalation timelines. Replaces a manual tracking effort that was prone to delays and inconsistency, saving significant time for Quality Analysts managing active abusive contact cases and ensuring the investigation
- Consistently exceeded monthly audit targets with zero score clarifications. Developed an AI-powered audit tool that improved audit speed, accuracy, and consistency, directly influencing a shift in org-level audit strategy from advisor-focused defect detection to systemic process improvement. Expanded AI tool usage beyond Work Events domain into Time domain and Pay and Compensation domain. Created an official walkthrough video for Employee Experience audits following the pilot launch to support t
- Identified broken logic in the Employee Experience Audit (EEA) dashboard that was pulling incorrect data and producing unreliable reporting. Escalated the issue through the appropriate channels, partnered with the Program Manager to investigate, and drove resolution that restored confidence in dashboard reporting for the team and leadership.
- Designed and delivered a 2-hour AI workshop for Quality Analysts covering AI fundamentals, practical prompt engineering techniques, and step-by-step prototype building exercises. Workshop received 100 percent positive feedback, with the majority of participants rating it as "very useful" and validating the pacing and content clarity. Delivered live to 15 to 20 participants with recordings shared for broader team reach.
- Created a Quick Suite automation that retrieves manager and skip-level manager email IDs using employee logins, eliminating repeated Phone Tool lookups during security verification audits. Enabled batch processing for up to 10 logins simultaneously, reducing domain-related audit errors and significantly improving audit turnaround time and consistency.
- Built a structured decision tree application for handling post-employment queries, providing Quality Analysts with a guided resolution path for alumni-related contacts. Accelerated case resolution time and standardized responses across the team, reducing inconsistency and ensuring compliance with post-employment handling guidelines.
- Influenced QA audit strategy and tooling adoption without formal authority by consistently demonstrating measurable outcomes and data-backed results. Earned senior leadership visibility, including direct outreach from an L6 leader regarding a potential domain transition based on sustained performance and impact. Maintained trusted relationships across QA, Operations, and Program stakeholder groups through transparency, delivery consistency, and data-driven recommendations.
- Designing a scalable audit workflow that leverages AI to proactively identify systemic process gaps and surface high-impact improvement opportunities across the contact center. Presented to leadership as a strategic quality initiative, positioning AI as a driver of process intelligence rather than a tooling experiment.
- Designing a solution to allow employees to reconnect to a new advisor with prior chat history intact when a chat session is disconnected. Aims to reduce Average Handle Time (AHT), prevent repeated employee questioning, improve employee experience, and eliminate unfair Handle Missed Defects (HMDs) caused by disconnects.
- Building a thematic audit framework specifically targeting disconnected chat scenarios. Identified the lack of resolution documentation as a recurring failure pattern and designed audit standards to improve consistency, accountability, and quality outcomes in disconnected contact handling.
Senior Process Executive - Infosys BPM - Bangalore, India
(2016-10 - 2019-04)
Managed high-volume employee and customer inquiries while maintaining service-level commitments. Investigated issues, performed detailed research, and escalated complex cases for resolution. Prepared operational reports, analyzed performance trends, and supported continuous improvement initiatives. Collaborated with internal stakeholders to improve customer experience and operational effectiveness.
