Ocholi Idakwo

Reduced data infrastructure deployment time by 83% (from 3 months to 2 weeks) using AWS CodePipeline and blue/green deployments, enabling rapid global feature launches with zero service disruptions.

Engineered a modern AWS-based S3 data lake, reducing query latency from hours to minutes and enabling real-time 360-degree user analytics across Meta's diverse platforms.

Developed a real-time fraud detection system processing over 600,000 interactions per second and 2 TB of daily data, significantly improving fraud detection capabilities.

Optimized daily ETL processing time by 50% (from 8 to 4 hours) while handling 500 million records, improving overall data processing efficiency for global operations.

Established a robust data quality monitoring system performing over 400 million daily checks, preventing discrepancies in 5 million user interactions through proactive alerting.

Developed a predictive maintenance system for 10,000+ machines, reducing failure incidents by 40% and generating $1.5M in annual maintenance cost savings.

Engineered an NLP optimization pipeline for customer service, processing over 100 million transcripts to identify 25 unique complaint patterns, improving customer satisfaction.

Automated a time series forecasting system for retail inventory, achieving 2-5% accuracy across 4 million SKUs and 500 stores, saving $2M annually through optimized stock.

Designed and deployed a real-time anomaly detection system for financial transactions, scoring over 50 million transactions daily with <200 ms latency, preventing $5M in annual fraud losses.

Implemented a computer vision system for PCB quality control, processing 100,000 PCBs weekly with 95% accuracy, saving $500K annually by reducing faulty shipments.