At JPMorgan Chase, I improve risk and compliance systems for FX and crypto trading, expanding stress-test coverage, reducing trade-processing errors, and moving failed-trades reporting from Excel to Parquet to cut generation time from 30 minutes to under 5 minutes.
Previously at McKinsey & Company, I built audit-log systems with DynamoDB Streams and AWS Lambda, improving real-time processing speed by 30%. I also deployed Python cloud applications with Terraform and GitHub Actions, reducing deployment time by 40%, and developed ML-driven, Gen AI-powered SaaS solutions using Flask on AWS.
My earlier work at Hashedin by Deloitte included Django REST APIs, GraphQL workflows, AWS integrations, RBAC, and ReactJS interfaces. I bring 6+ years of experience building reliable microservices, RESTful APIs, cloud-native systems, and automated delivery pipelines.
