19 of 19 Remote/Hybrid Metadata Jobs in the South West

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

Designing, supporting, and guiding the upgrade, management, decommissioning, and archiving of data in line with data policy Defining and maintaining data technology architecture, including metadata, integration, BI, and data warehouse architectures Producing, maintaining, and reverse-engineering data models to meet organisational and programme needs Providing input into and maintaining data … dictionaries and metadata repositories Undertaking data profiling and source system analysis to support effective data use Ensuring data solutions comply with governance, security, and assurance requirements Monitoring compliance with data standards and assessing the impact of breaches Supporting multidisciplinary delivery teams with clear data insights and architectural guidance Communicating effectively ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...

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 … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal 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 serving. ...