8 of 8 Metadata Jobs in the City of London

specific data needs. Proven track record in creating and executing strategic roadmaps and implementation plans. Hands-on experience with data governance, quality management, metadata, lineage, and master/reference data strategies, including compliance. Proficiency in using data management platforms such as Purview, Collibra, and Informatica. Experience with cloud-based data ...

technical audiences. Strong stakeholder engagement and self-management skills. Familiarity with cloud platforms (AWS preferred) and public sector data practices. Experience with metadata tools, ontologies, data platforms (e.g. lakes, meshes). Use of tools like Visio, Sparx, or frameworks like TOGAF. Knowledge of technical specs, data catalogues, and standards assurance. ...

authoritative data sources Facilitate structured sessions with SMEs and data office to validate definitions, resolve discrepancies, and capture requirements Define and embed modelling standards, metadata requirements, and quality controls aligned to the data governance framework Operate within a factory model, working in an iterative, high-throughput approach to deliver multiple ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...