Gideon Ler

Led design and implementation of a threat intelligence platform processing over 1M indicators daily, enabling consulting teams to perform faster investigations and reducing manual analysis effort by 40%. Redesigned intelligence enrichment workflows to improve processing throughput by 20x and expand intelligence coverage. Delivered integrations between external intelligence providers and internal platforms, improving data accessibility and interoperability across consulting and investigation teams. Collaborated with AI/ML teams to operationalize malware classification and phishing detection solutions for customer-facing use cases. Deployed Model Context Protocol (MCP) services to create a unified data access layer, reducing query complexity for downstream teams and improving cross-product integration efficiency. Automated IOC expansion using VirusTotal hash pivoting, strengthening threat intelligence coverage for engagements. Conducted exploratory big data analysis to translate findings

Facilitated data migration by creating Python Spark jobs to perform ETL for over 124GB of transactional data from Amazon S3 into the PEGA system, using AWS Glue and PySpark. Planned and conducted performance tests for the UAT server using Apache JMeter, coordinating with stakeholders for test deployment. Improved system throughput by 25% through performance testing and bottleneck resolution.