Vaishnavi Muruganandam

Program Details

Amazon

Chennai

04.2020 - Current

Developed project plans, identified risks, set objectives and monitored progress towards completion.
Collaborated with data scientists, program managers, and the SWOT team to integrate NER slotting components into FR annotation, creating a framework and implementing it in the Mercury tool. Added 97 slot labels to the annotation template, enabling 60K OPTIMA annotations for direct use in model training.
Established a DAH program to identify errors and fix bugs in the process, leading to a significant quality improvement from 87% to 94%. This initiative helped streamline operations and enhance overall process performance.
Developed the APS platform to improve DA performance by providing monthly visual updates on individual rankings versus team performance. This initiative increased transparency, bridging the gap for 46% of DAs who lacked performance insights, and achieved 100% satisfaction among DAs seeking to improve their performance.
Worked on the key launches, including Rufus, Blue, Show*, Shopping Ambiguity, CAEC-List, WSIRN-Book Recommendation, Playful Shopping Request, etc., driving impactful improvements across multiple programs.
Developed an automated dashboard to track DA performance, incorporating factors like leave, NPT, and OT, saving 26 hours of manual effort per week across the IND site and improving accuracy and efficiency.
Led the training program for the operations team where the program covers end-to-end onboarding plan with performance and quality monitoring mechanism. Through this initiative, we successfully onboarded 122 HCs across the SEA, BLR, MAA, DEL, and OTP teams.
Oversees the publication of the Rufus IND site scorecards (MAA, BLR, DEL), collaborating with internal and external stakeholders to ensure the timely delivery and accuracy of performance metrics. Streamlined the process, reducing turnaround time, and contributed to the stack review by aligning data with key parameters, and integrating sources for the successful completion of H1 2024.
Identified a gap in tracking TOT, and uncovered a 35% deviation from expected AHT for data analysts. Collaborated with the BA team to develop a T-PAM metric dashboard that improved time tracking and reduced annotation time discrepancies. Notably, the annotations completed with less AHT decreased from 11.13% to 3.13%, which has impacted the quality of the ops team from 89% to 94%, and the time bound of taking excess AHT has fallen from 31.02% to 10.67%, with significant improvements in utilization.
On-boarding AQ and TD programs in the UK and IN, adapting US workflows, and securing stakeholder approvals. Facilitated cross-regional alignment, managed the transition to the BLR team, and supported multiple markets, achieving over 90% process quality, and contributing to the successful launch of Rufus in the OTP and KIX sites through targeted training sessions.
Collaborated with the tooling and BI teams to launch a dashboard that enhances data privacy by limiting access to PII for Alexa's data analysts. The work resulted in a successful dashboard launch, driving improved data handling and compliance.
Led onboarding plan for BCN site, organizing 15 sessions for new team and operations managers across multiple sites. Facilitated cross-site collaboration, ensuring efficient knowledge sharing and standardization of practices, resulting in a successful and impactful onboarding program in BCN.
Analyzed overtime data over six months, identifying a 23% underutilization of recorded overtime hours. Collaborated with the HR team to develop SOPs and recommendations for improved tracking and compliance, leading to a significant reduction in unauthorized overtime, and an estimated savings of approximately 149 hours per month.
Led the implementation of the Annotator Quality report across Rufus IND sites (MAA, BLR, DEL), collaborating with TMs and audit teams to address dispute mechanisms and enhance quality tracking.