Brahim Nid-Youssef

I’m a Data Scientist with 4+ years at Cisco, specializing in Generative AI, LLM integration, and predictive modeling. I build solutions that turn complex data into reliable decisions, with predictive-input reliability >99%.

At Cisco, I led Renewal Risk 3.0 across 6+ security product lines (Duo, Umbrella, Firewall, ISE), improving risk-scoring accuracy by 15% and enabling proactive retention. I also architected and deployed LLM-based solutions for TAC security mitigation planning, reducing manual analysis time by 25% and accelerating response times for enterprise clients.

I designed TAC Semantic Views using Cortex Analyst to enable natural-language queries, cutting time-to-insight by ~70% and reducing manual workflows by 25%. I improved data validation and pipeline controls for security telemetry, reducing downstream discrepancies by 50% through production validation checks.

I partner closely with Product and Engineering to deliver Catalyst Center analyses and RR dashboards, contributing to a 35% increase in executive decision accuracy. Earlier, at Trane Technologies, I developed pricing-optimization models that generated $210K in incremental revenue and improved rebate-processing accuracy by 21% using machine learning.