1 to 25 of 264 Validation Jobs in Scotland

requirements definition through to testing, UAT planning, implementation, and adoption.Partner with AI engineers, architects, product owners, and delivery teams to support the design, development, validation, and rollout of AI-enabled capabilities.Contribute to Agile and hybrid delivery programmes through backlog refinement, sprint planning, stakeholder management, reporting, and governance activities.Support responsible ...

data models, schemas, and data governance frameworks to support analytical and operational needs.Utilise SQL and scripting languages (Python or R) for data extraction, transformation, validation, and integration across diverse data sources.Project Management & Stakeholder EngagementManage project timelines, scope, and deliverables effectively, ensuring successful outcomes and client satisfaction.Collaborate closely with cross-functional ...

impacts across systems, processes, data and teams, identifying risks, assumptions, constraints and dependencies. Work with test teams and stakeholders to support test scenario definition, validation, defect triage and solution acceptance. Champion customer and colleague needs throughout analysis and delivery, ensuring solutions are practical, usable and aligned to the intended experience. ...

change impacts across systems, processes, data and teams, identifying risks, assumptions, constraints and dependencies.Work with test teams and stakeholders to support test scenario definition, validation, defect triage and solution acceptance.Champion customer and colleague needs throughout analysis and delivery, ensuring solutions are practical, usable and aligned to the intended experience.Collaborate effectively ...

libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining, monitoring and reproducible delivery.Experience using cloud ...

libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining, monitoring and reproducible delivery.Experience using cloud ...

applicable o JSON, XML, XSLT, XPath and schema-based transformations • Implement robust error handling, replay, recovery and operational support patterns covering technical failures, business validation failures, rejected records and downstream availability issues. • Support performance tuning for high-volume integrations, including batching, pagination, payload optimisation, parallel processing and appropriate ...

workflows.Use Python and SQL to clean, model, and analyse data; deliver self-service analytics through governed semantic models and reporting layers.Lead UAT and business validation for analytics outputs and AI products.Support teams in moving from manual reporting to governed, AI-enabled analytics.What You'll BringExtensive experience leading business stakeholders ...

continuous improvementDrive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while setting consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patternsApply software development lifecycle toolchain knowledge, including enterprise-authorized AI-assisted development and automation ...

HCMProcurementSCMDeep knowledge of Oracle Fusion data models, table structures, subject areas, and data dictionaries.Advanced SQL and PL/SQL skills.Strong understanding of data extraction, validation, reconciliation, and reporting architecture.Experience designing scalable, supportable, and high-performance reporting solutions.Ability to translate business requirements into reusable technical solutions.Desirable SkillsExperience with:Business Intelligence Cloud ...

delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools ...

communication skills, providing clear updates to stakeholders across levels.Strong collaboration skills across lines of business, with demonstrated use of enterprise-authorized AI and disciplined validation/data-sensitivity practices.Preferred qualifications, capabilities, and skillsExperienced in using Business Driven Development/Test Driven Development test methodology or test case automation.Experienced in using ...

skills, providing clear updates to stakeholders across levels. Strong collaboration skills across lines of business, with demonstrated use of enterprise-authorized AI and disciplined validation/data-sensitivity practices. Preferred qualifications, capabilities, and skills Experienced in using Business Driven Development/Test Driven Development test methodology or test case automation. ...

delivery speed, and operational outcomes (e.g., AI‐assisted code review/refactoring, test strategy acceleration, incident/root‐cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team Applies knowledge of tools within the Software Development Life ...

delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the teamApplies knowledge of tools within the Software Development Life Cycle ...

Proof of Concept demonstrationsFacilitate requirements gathering, design, and gap analysis workshopsOversee functional configuration and provide technical input on integrations and data migrationConduct solution validation and user trainingProvide post go-live functional support and ongoing advisory servicesEnsure timely and quality project delivery while managing client expectationsQualificationsAbout YouYou’ll be a trusted ...

delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.Applies knowledge of tools within ...

delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools ...

enterprise programmesConfigure Oracle Cloud instances for client Proofs of Concept and demonstrationsRun requirements gathering, design, and gap analysis workshopsLead application configuration and solution validation workshopsDrive functional ownership of:Data migration activitiesIntegrations with peripheral systemsTesting strategy, script creation, and UAT supportDeliver high-quality reporting solutions using:Oracle Transactional BI (OTBI)Financial ...

expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures. Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern ...

scale.Deep expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures.Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment.Good foundation in statistics, probability, optimization, experimentation, and applied machine learning.Advanced proficiency in Python and modern AI frameworks, including ...

PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production environments.Familiarity with advanced AI techniques such as deep learning, natural language processing (NLP), computer vision, reinforcement learning, and Generative AI (e.g. ...

PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production environments.Familiarity with advanced AI techniques such as deep learning, natural language processing (NLP), computer vision, reinforcement learning, and Generative AI (e.g. ...

testing web applications, APIs, and integrated systems.· Experience writing and executing SQL queries, with the ability to understand database structures and interrogate data for validation and analysisDesirable Skills & Experience:· ISTQB certification or equivalent.· Experience testing within an Intelligent Transport Systems environment.· Experience implementing test automation within CI/CD pipelines. ...

solutions meet defined product requirements, performance standards and business objectives. Support the successful commercialisation of machine learning technologies by contributing to product integration, verification, validation and deployment activities. Work with clinical research partners and healthcare stakeholders to evaluate the clinical effectiveness and diagnostic performance of machine learning models and analytical ...