26 to 50 of 173 Anomaly Detection Jobs in the UK

models from development into production environments.Technical SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection.Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.SQL and large-scale data analysis.Cloud-based data science platforms and MLOps practices.Data ...

science, CRM, machine learning, and other data consumers across the organization.Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection.Ensure enterprise data integrity, validation, documentation, and governance.Platform & Software EngineeringWrite production Java and Python code across our evolving platform stack — from data ingestion ...

machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack — from data ...

ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation … ideally genomic data. Developing models, algorithms or rule-based systems that support human decision-making, ideally where explainability, auditability and risk management are important. Anomaly detection, behavioural analytics, security monitoring or detection engineering. Risk quantification methods from fields such as actuarial science, epidemiology, operational research ...

deploying machine learning models for risk scoring, compliance prediction, churn analysis and contractor performance analytics Building and deploying LLM-based solutions for text analytics, anomaly detection and automated compliance checks Working with Engineering and Product teams to integrate models into production environments across AWS and Azure Using ...

operational data.Knowledge of cloud platforms (Azure, AWS, or GCP) and big data technologies.Strong understanding of data pipelines, ETL processes, and data quality management.Experience with anomaly detection, forecasting, and predictive maintenance applications.Solid understanding of statistical analysis, hypothesis testing, and experimental design.Ability to develop and deploy machine learning models ...

regulatory considerations.Familiarity with modern data infrastructure and architecture (APIs, pipelines, cloud platforms), with exposure to AI/ML or LLM-based enrichment solutions for anomaly detection and automation.Exposure to Agile methodologies such as Scrum or Kanban.Awareness of emerging trends in Private Markets data, including the complexities ...

custom microservices Pilot and scale emerging technologies such as Generative AI where appropriate. Implementing AI/ML models for exception management, document classification, anomaly detection, and operational intelligence Identify areas for tech‐driven innovation and rapidly prototype solutions with internal or vendor teams Evaluate and select external ...

service provisioning.Lead SAP technical architecture decisions for hybrid and cloud-native environments (RISE, hyperscalers).Drive adoption of AIOps for SAP operations (predictive monitoring, anomaly detection, auto-remediation).Implement automation for repetitive BASIS operations (system health checks, patching, job management).Leverage AI/ML tools for incident prediction ...

business domains — defining, validating, and owning the definitions, metrics and models that drive decisions.Apply machine learning to real business problems: predictive modelling, classification, segmentation, anomaly detection, and forecasting.Use LLMs and generative AI to build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering ...

business domains — defining, validating, and owning the definitions, metrics and models that drive decisions.Apply machine learning to real business problems: predictive modelling, classification, segmentation, anomaly detection, and forecasting.Use LLMs and generative AI to build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering ...

business domains — defining, validating, and owning the definitions, metrics and models that drive decisions.Apply machine learning to real business problems: predictive modelling, classification, segmentation, anomaly detection, and forecasting.Use LLMs and generative AI to build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering ...

ecosystem. - Real-time trend monitoring and predictive analytics. - Customer intelligence, behavioural segmentations and personalisation. - Self-Service Business Intelligence. - Early warning systems, alerts and automated anomaly detection across payment journeys. The Data & AI Senior Product Owner is responsible for identifying gaps and opportunities for new data ...

ecosystem.• Real-time trend monitoring and predictive analytics.• Customer intelligence, behavioural segmentations and personalisation.• Self-Service Business Intelligence.• Early warning systems, alerts and automated anomaly detection across payment journeys.The Data & AI Senior Product Specialist is responsible for identifying gaps and opportunities for new data and AI services ...

ecosystem.• Real-time trend monitoring and predictive analytics.• Customer intelligence, behavioural segmentations and personalisation.• Self-Service Business Intelligence.• Early warning systems, alerts and automated anomaly detection across payment journeys.The Data & AI Senior Product Specialist is responsible for identifying gaps and opportunities for new data and AI services ...

business priorities.Build and optimize monitoring, observability, and alerting capabilities using tools such as Prometheus, Grafana, AppDynamics, and Splunk.Apply AIOps capabilities to improve event correlation, anomaly detection, root cause analysis, predictive insights, and proactive issue prevention.Partner with engineering, infrastructure, production support, security, and risk teams to ensure developed ...

/v4 Foundation or experience aligning QA with service management practices. Experience applying AI/ML in Quality Engineering, including test optimisation, defect prediction, anomaly detection or analytics-led assurance. Experience with enterprise orchestration tools such as Control-M, Autosys or equivalent scheduling platforms. Experience with master ...

consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI‐assisted data tooling (AI‐powered cataloguing, natural language querying, automated data quality) where ...

architecture that serve trading, risk, compliance, analytics and many product teams.Drive adoption of AI automation and intelligent workflows — automating data quality checks, pipeline orchestration, anomaly detection, and self-healing infrastructurePartner with ML/AI, analytics, and product engineering teams to deliver platform capabilities that accelerate their workEvolve ...

version control (Git), testing frameworks, and infrastructure as code (Terraform). Demonstrated ability to embed data quality, observability, and alerting into pipelines (automated validation, anomaly detection, monitoring). Experience leading technical design sessions, owning architecture decisions, and communicating trade offs clearly to both technical and non technical ...

remediation logic. Improve enterprise tool signal quality by integrating vendor health data and usage telemetry into AIOps systems. Support tuning of alert correlation and anomaly detection models for enterprise services. Track improvements in MTTR, alert noise reduction, automation coverage, and platform uptime. Requirements Bachelor’s degree ...

data pipelines’ SLA and dependency management.Writing technical documentation for data solutions, and presenting at design reviewsSolving data pipeline failure events and implementing sound anomaly detection Working with various teams from analytics to product owners and front end developers on tracking solutions and solving technical challengesLeading medium ...

between regulatory intent and technical execution. In this role, you will serve as the global second-line authority and owner of financial crime detection models, risk analytics, and automated control frameworks. You will own the global methodology, thresholds, and data-scoring models used to identify and mitigate financial … native, API-first environment where transaction decisions must be executed algorithmically in milliseconds.Proven track record of moving advanced machine learning, neural networks, or behavioral anomaly detection models out of testing and into live, global compliance operations safely and transparently.Experience utilizing graph databases and link analysis to identify ...

preventative controls. Drive adoption of automation-first principles, reducing dependency on human-driven processes. Contribute to AI-driven operational use cases, including event correlation, anomaly detection, noise reduction, operational insights, and automated remediation. Ensure AIOps capabilities are grounded in reliable telemetry, clear control boundaries, and measurable operational … Operational Excellence Define standards for telemetry, monitoring, alerting, and operational visibility across all critical systems. Ensure services are observable, measurable, and support proactive detection of issues. Improve operational readiness, incident response effectiveness, and time-to-recovery through engineering solutions. CI/CD & Platform Integration Contribute to the design ...

champion within Corporate FP&A, defining and executing the AI roadmap for planning, forecasting, reporting and process automation.Embed AI-enabled forecasting, anomaly detection, driver-based scenario modelling and natural language query capabilities into the EPM and reporting stack.Partner with the CIO, Data & AI teams and Finance leadership ...