gnvikas02
About Candidate
• Monitor production transaction systems processing 500,000+ daily transactions across multiple payment
switches and projects, ensuring 99.9% system availability and sub-5-minute issue detection.
• Analyze abnormal transaction decline patterns using SQL-based log queries, and investigated ISO 8583 message
flows, routing behavior, and response codes through detailed log analysis (router, security, and network logs) to
pinpoint performance bottlenecks.
• Investigate batch decline patterns across 50–1,600+ transactions per cycle, reducing mean time to resolution
(MTTR) by 50% through structured root cause analysis and data-driven troubleshooting.
• Perform continuous error log monitoring and correlate COMM timestamps, response codes, and last-5 backup
transactions to detect failure patterns in live eCom and POS payment systems.
• Prepare daily operational reports and incident summaries for internal stakeholders, tracking transaction health
metrics, recurring error codes, decline trends, and resolution status.
Location
Education
Computer Science Graduate
Work & Experience
• Monitor production transaction systems processing 500,000+ daily transactions across multiple payment switches and projects, ensuring 99.9% system availability and sub-5-minute issue detection. • Analyze abnormal transaction decline patterns using SQL-based log queries, and investigated ISO 8583 message flows, routing behavior, and response codes through detailed log analysis (router, security, and network logs) to pinpoint performance bottlenecks. • Investigate batch decline patterns across 50–1,600+ transactions per cycle, reducing mean time to resolution (MTTR) by 50% through structured root cause analysis and data-driven troubleshooting. • Perform continuous error log monitoring and correlate COMM timestamps, response codes, and last-5 backup transactions to detect failure patterns in live eCom and POS payment systems. • Prepare daily operational reports and incident summaries for internal stakeholders, tracking transaction health metrics, recurring error codes, decline trends, and resolution status.
• Cleaned and standardized 5 NLP/NLI datasets totaling 2,500+ records, improving data consistency and reliability by 35% for transformer model evaluation. • Evaluated 5 transformer-based NLI models, documented accuracy comparisons across datasets, and presented findings to technical team for production model selection.