1 to 25 of 29 Use Case Jobs in Surrey

forecasting, optimization support, and conflict detection. Teaching & Learning: content summarization, tutoring assistants, accessibility tools, and feedback synthesis respecting academic integrity. Student 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 … Finance (ERP), and identity platforms (e.g., Azure AD). Govern AI responsibly Implement a practical AI governance framework that includes a use case register, risk scoring, impact assessments, model documentation, and audit trails. Ensure compliance with GDPR, accessibility standards (e.g., WCAG), information security policies, and emerging ...

forecasting, HR, sales, and billing systems) into the data warehouse Assist in designing and maintaining data models that support automated reporting and analytics use cases Reporting Automation & Enablement Help automate recurring finance and management reporting processes to reduce manual effort and improve accuracy Enable self-service and scalable ...

Azure (multi-cloud a bonus) • Experience with time-series, telemetry, or high-volume operational data • Solid data modelling skills for analytics and ML use cases • Strong focus on data quality, testing, and reliability • Experience with CI/CD, IaC, version control, and observability • Security-aware mindset and disciplined ...

landing zone setup, environment readiness, integrations, governance, and delivery management across diverse client workstreams (HR, Payroll, Workforce, Clinical, Reporting), implementation of reporting & analytics use cases for end users. You will work closely with client programme leadership, business SMEs, cloud architects, data engineers, and third party providers (Microsoft, Oracle ...

practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details ...

Face. Collaborate with data scientists and software engineers to create scalable AI-powered applications. Fine-tune and evaluate large language models for specific use cases and domain adaptation. Optimize retrieval and generation workflows for performance, accuracy, and cost-efficiency. Stay updated on the latest advancements in generative ...

systems. The role is hands-on and end to end, covering data preparation, model development, and deployment across traditional ML and LLM-based use cases. You will work on real production problems rather than research-only work, owning models from first iteration through to live deployment. You will ...

functionality. Ensure compatibility and optimised performance across iOS and Android platforms. Contribute to AI-driven feature development and R&D initiatives, exploring innovative use cases for spatial data. Team Collaboration & Growth Participate in code reviews and engage in regular 1:1 mentorship. Actively research ecosystem developments and advancements ...

Proven hands-on experience delivering Microsoft Copilot and/or Copilot Studio solutions Experience building and deploying AI agents aligned to real business use cases Strong stakeholder engagement skills – able to shape scope, not just take tickets Comfortable working in evolving environments with partial requirements and high visibility ...

evaluation frameworks across performance, robustness, safety, and bias Own deployment: GPU optimization, latency reduction, scaling policies Shape early product direction, experiment with new use cases, and build AI-powered experiences from zero Explore frontier techniques: retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, multimodal models What ...

evaluation frameworks across performance, robustness, safety, and bias Own deployment: GPU optimization, latency reduction, scaling policies Shape early product direction, experiment with new use cases, and build AI-powered experiences from zero Explore frontier techniques: retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, multimodal models What ...

senior leadership team, you will: Take ownership of the internal AI agenda and acceleration roadmap Define and prioritise high-impact AI use cases across the business Help shape and package AI-enabled services built on HubSpot's platform Create clear implementation blueprints that can be delivered repeatedly ...

Work closely with Marketing on campaigns, events, and account-based initiatives Develop a strong understanding of cyber-physical risk, industrial environments, and customer use cases Consistently hit activity, meeting, and pipeline contribution targets What They're Looking For: Must be Spanish or French speaking Experience in B2B outbound ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

technical requirements Lead stakeholder engagement, facilitating workshops, interviews, and design sessions to uncover pain points, assess opportunities, and define automation and AI-enabled use cases Collaborating with development teams to prioritize and deliver AI and automation solutions aligned to business value and strategic outcomes Design, evaluate, and validate … technical teams alike to influence outcomes and drive alignment Awareness of ethical and regulatory implications of AI adoption, including bias, transparency, and responsible use Strong communication and storytelling skills, with the ability to simplify complex technical concepts for non-technical audiences Consulting mindset professional, adaptable, and comfortable working ...

product functionality and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams … iteration. Partner with commercial and operational teams to identify and automate processes that can be enhanced through AI tools. Ensure responsible and secure use of AI through data governance, model guardrails, and compliance measures. About You Deep expertise in Python, machine learning, and data science. Experience building, deploying ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...

driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices … 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. End-to-end MLOps experience, including ...