Summary
Bryan Feeney is a Principal Data Scientist based in Edinburgh with 12 years of experience turning large-scale time-series and NLP problems into production products for energy and advertising domains. He has repeatedly delivered high‑impact ML systems—from a deep-learning appliance detection model with 90/90 precision/recall and 10‑second power estimates, to anomaly-detection and forecasting pipelines operating on hundreds of thousands to millions of European users. Technically fluent across the scientific Python stack, TensorFlow, Spark, Hadoop/Cassandra ecosystems and AWS SageMaker, he bridges research and engineering to ship reliable, scalable analytics. A practiced team builder and manager, he introduced agile practices and cross-functional guilds to improve delivery and collaboration. His background spans both academic probabilistic modelling (PhD work and variational inference) and pragmatic production engineering (Docker, Kubernetes, Kafka, Aurora), enabling him to translate novel Bayesian and deep-learning methods into deployable services. Unusually, he combines deep research instincts with hands-on product ownership—having reviewed patents, negotiated acquisition earn-outs, and led projects funded by DESNZ.
12 years of coding experience
13 years of employment as a software developer
B.Sc. Computer Science, B.Sc. Computer Science at University College Cork
University College London