26 to 50 of 145 Anomaly Detection Jobs in England

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 ...

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 ...

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 ...

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 ...

other motorsports series. Our software combines many capabilities, including data capture, visualisation and modelling of real time and historic data for detailed analysis, reporting, anomaly detection and enabling the best strategic decisions to be made. Through clean and consistent coding, you will contribute to optimise our methods ...

incident, backup, resilience and monitoring controls. Practical experience applying AI, Agentic AI, AIOps or intelligent automation to operational use cases such as incident triage, anomaly detection, runbook automation, knowledge search, root cause support or service desk workflows. Knowledge of observability and reliability practices, including SRE principles, service ...

OpenTelemetry traces, change events, and runbooks to accelerate Mean Time to Detection (MTTD) and Resolution (MTTR). Safe Production Automation: Develop proactive anomaly detection and Human-in-the-Loop (HITL) remediation workflows with rigorous safety, security, and quality guardrails. Reliability & Scalability Engineering: Partner with application ...

Dynamics) Exposure to fraud detection, financial crime analytics, or compliance monitoring Experience applying statistical and advanced analytical techniques (e.g., hypothesis testing, regression, anomaly detection, or machine learning) Experience working with version control systems (e.g., Git) and structured development environments (e.g., VS Code or similar), with ...

scope spans a wide variety of problems in computational advertising including brand safety classification, content suitability scoring, risk hunting and proactive threat detection, viewability prediction, Made-for-Advertising (MFA) detection, malvertising identification, and privacy-preserving measurement and integration. We are looking for an exceptional Principal Applied … production scale Experience in computational advertising, ad tech, content moderation, trust & safety, or fraud/abuse detection Expertise in adversarial machine learning, anomaly detection, or security-oriented ML applications Familiarity with industry standards: MRC accreditation, TAG certification, brand safety frameworks, IAB content taxonomy Experience with ...

ownership and exposure to cutting-edge technologies. The Role Build scalable data pipelines using Microsoft Fabric and Databricks Develop machine learning solutions across forecasting, anomaly detection, recommendation systems, and information extraction Work with structured, semi-structured, and document-heavy datasets Create reusable data assets and analytical products ...