1 to 25 of 39 Permanent Metadata Jobs in the East of England

analytics outputs Data Governance & Standards Apply established data governance, security, and data management standards in all work Support data quality initiatives, including definitions, metadata, and validation rules Collaborate closely with data owners and subject matter experts to ensure accurate interpretation of data Contribute to continuous improvement of analytics standards, templates ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

Support & Wellbeing: intelligent case routing, early warning signals, and proactive nudges designed with strong ethics and safeguarding. Research Administration: grant discovery, compliance support, and metadata enrichment. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance ...

useful (such as DAMA’s DMBoK & CDMP, EDM Council’s DCAM), including but not limited to: Regulatory compliance (GDPR, CCPA) Data quality and metadata management AI data governance protocols Data lifecycle and classification Evidence, experience and understanding of data strategy, management concepts and associated business processes and tools - including Data ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

TimeXtender delivers secure, trusted, AI-ready data for every decision. Our metadata-first platform enables mid-sized enterprises to build future-proof data infrastructure 10x faster than traditional methods. By automating the complex layers of data ingestion, preparation, and delivery, TimeXtender provides a secure foundation for analytics and AI across ...

help manage and optimise campaigns across multiple sectors. Key Responsibilities Conduct detailed keyword research, competitor analysis, and market insights Optimise on-page elements including metadata, content structure, and internal linking Support technical SEO audits and coordinate with developers to implement recommendations Monitor and report on organic performance using leading ...

Data Engineer £53,000 per annum Bedford Permanent Hybrid Working Role Overview Join us at the Money and Pensions Service (MaPS) as a Data Engineer where you will design and implement data pipelines to connect ...

monitor and report on data quality metrics. Data Asset Management: Maintain and optimise the data catalogue, ensuring essential data sets are identified and metadata is accurate. Data Management Processes:: Implement wider data management competencies into processes such as data quality, metadata management, and master data management. Learning and Development: Support … Data Governance Knowledge: Up-to-date knowledge of data governance theory, methodologies, and practical considerations. Technical Knowledge: Understanding of data management, including data quality, metadata management, and data modelling. Proactivity and Problem-solving: Proactive, self-motivated, with strong problem-solving skills. Stakeholder Management: Excellent communication skills and experience in managing ...

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. ...