Farida Aliyeva

I’m an AI Consultant and Senior Data Scientist with 5+ years of experience building scalable machine learning systems that drive real-world outcomes across AgTech and EdTech domains. I specialize in designing and deploying end-to-end AI/ML pipelines - from data ingestion and modeling to deployment and monitoring - helping organizations turn raw data into intelligent systems that support decision-making and innovation. Recently, I led the development of geospatial disease and pest risk models for the Ministry of Agriculture of Azerbaijan in collaboration with McKinsey's ACRE team, integrating Meteoblue weather data, NDVI satellite imagery into real-time Tableau dashboards. This work delivered operational insights at scale, supporting government-level agricultural planning. My technical expertise spans geospatial ML, time-series forecasting, and NLP (including multilingual text in German), using tools like Python, PyTorch, AWS (SageMaker, Lambda), Docker, PostgreSQL, and MongoDB. I focus on building production-grade systems with CI/CD automation, parallel data processing, and scalable infrastructure. As a consultant, I help businesses adopt AI not just as a technology, but as a strategic lever. Whether it’s automating workflows, extracting value from unstructured data, or designing resilient predictive systems, I bridge the gap between AI capabilities and real-world application.