Gabor K.

Most companies sitting on years of operational data still can't answer their most important questions: What will fail next? Where are we losing money? What should we do differently? I build the AI and ML systems that answer those questions — reliably, in production, not just in demos. I'm a PhD-trained Senior Applied AI & Data Scientist with 10+ years of experience translating messy, fragmented, domain-specific data into working decision-support systems. My background spans industrial operations, healthcare, agriculture, retail, and oil & gas — environments where the data is imperfect, the stakes are real, and generic solutions don't work. I have delivered production-ready AI/ML systems across several domains: - Retail security: anomaly-detection logic for security gate systems in large retail environments - Agriculture: greenhouse sensor analytics and ML-based decision-support for tomato production optimization - Oil & gas: production analytics, decline-curve interpretation, geospatial analysis, and forecasting dashboards - Healthcare: claims analytics, patient population classification, risk grouping, and payment workflow automation - Travel & pricing: recommendation systems, demand analysis, and personalized pricing automation - Research: peer-reviewed AI/ML and NLP publications, university-level collaboration What I typically build: - Predictive models and forecasting systems for operational and business decisions - Anomaly detection and risk scoring pipelines - Time-series and sensor data analysis - Explainable AI workflows with interpretable outputs for non-technical stakeholders - End-to-end ML proof-of-concepts and production-ready solutions for startups and enterprise teams I work best with clients who have a real business or engineering problem and need someone who can navigate unclear requirements, imperfect data, and domain complexity — and deliver something that actually works.