James McEntee

Engineered an end-to-end AI citation audit system using Python and the Gemini API, processing 1,000+ queries across 8+ client domains to identify content gaps. Built a co-citation analysis model to map competitor relationships and normalize domain authority, delivering scores to prioritize link-building opportunities. Implemented a semantic content pruning framework with sentence transformers and clustering to identify 15 low-performing pages for removal; conducted 121-page technical SEO audits flagging issues (e.g., 87% missing H1 tags). Automated competitive analysis pipelines, reducing manual data collection time by ~60%, and delivered interactive Looker Studio dashboards for non-technical stakeholders.

Designed scalable data pipelines integrating Data ForSEO API to analyze 600+ iGaming domains; Built automated data collection and processing scripts; Conducted competitive analysis and KPI mapping for SEO & marketing intelligence.

Delivered strategic recommendations for an AI-driven cloud SaaS platform, contributing to a 35% reduction in infrastructure costs via dynamic resource allocation. Developed a PySpark preprocessing pipeline that reduced data cleaning time by ~50% for hybrid datasets. Implemented a Redis-MongoDB caching architecture with optimized queries, reducing dashboard latency by ~40%.