26 to 50 of 169 Anomaly Detection Jobs in the UK

Bristol, Warwick and LSE with industry partners. The role encompasses methodological, theoretical and computational research across institutions to deliver advances in statistical science for anomaly detection in streaming data. This is a full-time postdoctoral position of two years, with flexibility for part-time arrangements ...

scalability, and ease of maintenance. AI/ML Model Development Develop, train, and evaluate machine learning models that address core FinOps use cases: cost anomaly detection, spend forecasting, workload rightsizing recommendations, and commitment coverage optimization. Implement and maintain MLOps pipelines for model versioning, automated retraining, performance monitoring … drift detection as cloud usage patterns evolve. Experiment with and apply generative AI and LLM capabilities to FinOps workflows - such as natural language interfaces for cost querying, AI-assisted tagging remediation, or intelligent cost allocation suggestions. Collaborate with FinOps analysts to validate model outputs against business expectations, refining ...

than AI tooling alone. What you’ll be doing: Machine Learning & Advanced Analytics Develop machine learning models for forecasting, classification, recommendation, optimisation, clustering and anomaly detection. Apply statistical and machine learning techniques to analyse structured and semi-structured datasets. Perform exploratory data analysis, feature engineering, model training, validation ...

meet evolving analytical and business requirements. Drive high standards of data quality, integrity and governance through the implementation of automated validation, cleansing, monitoring and anomaly detection processes. Integrate, transform and harmonise data from a wide range of internal and external sources, including policy, claims, telematics and third ...

identify opportunities for analysis, modelling or product use. Develop, compare and validate appropriate statistical and machine-learning models for classification, ranking, recommendation, forecasting, anomaly detection, similarity or extraction problems. Use NLP, embeddings and LLM-assisted techniques responsibly for classification, entity resolution, information extraction, clustering and relationship discovery ...

Enterprise Solutions, shaping high-rigor analytical capabilities across a complex, regulated global financial-services environment. Design, build, and operate production-grade models for anomaly detection, variance analysis, drift detection, forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready. ...

licence optimisation, hardware rightsizing, capacity rebalancing, decommissioning, and vendor renegotiation Cost Governance Gaps — Assess and strengthen cost governance processes including approval workflows, budget controls, anomaly detection, and policy enforcement Data Normalisation — Normalise cost data from disparate sources into a unified cost model, enabling consistent reporting across business … months) based on value and feasibility Reporting & Dashboards — Design and recommend live/near-real-time cost dashboards with drill-down capabilities, trend analysis, anomaly alerts, and executive reporting views FINOPS PERSONA COLLABORATION As defined by FinOps.org, this role works with all key FinOps personas: Executives ...

into production environments.### Technical Skills* Python 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 ...

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 ...

communicating risk to executives while serving as a senior security advocate for sales, customer audits, and incident communications. You will own full-lifecycle detection and response (telemetry, automation, CI/CD detection-as-code, and MTTR/ATT&CK metrics) and serve as Incident Commander, running … team exercises and postmortem improvements. A major focus is driving AI security and internal AI governance: integrating LLMs/ML into SOC triage and anomaly detection, defending AI attack surfaces (agent activity, prompt injection, machine identities), hardening against AI-driven threats (phishing-resistant MFA, supply chain/ ...

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 ...

use.Raise reliability and data quality• Define data contracts, validation rules, freshness expectations, lineage, and service-level objectives for critical datasets.• Implement automated testing, anomaly detection, alerting, and observability across the data lifecycle.• Own production issues through diagnosis, recovery, root-cause analysis, and prevention.• Improve query performance, warehouse ...

approaches, and land insight in a way that drives action. Apply machine learning, analytics and reporting 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 ...

platform is adaptable to evolving global compliance standards. AI & Automation Integration:Apply knowledge of AI/ML concepts to explore and implement intelligent automation, anomaly detection, or data classification solutions within the regulatory reporting pipelines. Hands-On Development: Write clean, robust, and testable code using Java ...

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 ...

strategies, models and tooling, including chargeback and cost recovery, total cost of ownership and capacity planning. Experience applying statistical forecasting, time series analysis or anomaly detection to consumption or spend data. Experience articulating public cloud migration and modernisation economics to business and technology executives. Understanding of cloud ...

team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. As a forward deployed function, we partner closely with ...

systems, third-party tools, and logs; Develop and optimize data models for reporting, monitoring, forecasting, quality assurance, and experimentation; Implement validation checks, anomaly detection, and monitoring for key datasets and metrics; Define and enforce data definitions, SLAs, and ownership for critical tables and metrics; Improve the performance ...

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 ...

maintain automation scripts, deployment tooling, and operational workflows. Implement and support observability solutions, monitoring platforms, logging frameworks, and telemetry capabilities. Develop AIOps capabilities for anomaly detection, event correlation, alert noise reduction, and proactive issue identification. Create automated remediation processes, runbooks, and self-healing mechanisms to improve operational ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics. AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

vector stores, RAG, embeddings, tool surfaces. Python for data pipeline scripting and orchestration. Exposure to real-time analytics use cases - dashboards, alerting, and anomaly detection. Join TRG Screen and unlock your potential in an environment where innovation thrives, opportunities abound, and your contributions make a difference. ...

Automated fault detection, Root cause analysis, Dynamic RF optimisation, Automated channel selection, Automated power adjustments, Client steering, Service assurance automation, Network anomaly detection Experience leveraging machine learning and analytics to improve user experience, wireless performance, service availability and operational resilience. Ability to define architectures that ...

intelligent automation capabilities to reduce manual effort, improve operational efficiency, and enhance incident response workflows. Experience applying AI and automation solutions for alert correlation, anomaly detection, predictive monitoring, and service optimisation. Strong understanding of Site Reliability Engineering (SRE) principles, including service health, reliability, availability, observability, incident reduction ...