1 to 25 of 146 Permanent Anomaly Detection Jobs in London

user stories, acceptance criteria, and prioritized backlog items across the AIOps product lifecycle.Ownership of high-impact AIOps capabilities, including noise reduction, event management, correlation, anomaly detection, root cause analysis, predictive alerting, and self-healing remediation.Partner across Operations, infrastructure, SRE, platform engineering, service management, application teams, security … years of experience in product management, IT operations, SRE, observability, platform engineering, or related enterprise technology roles.Strong understanding of AIOps concepts, including event correlation, anomaly detection, root cause analysis, noise reduction, predictive analytics, and automated remediation.Experience defining product roadmaps, managing requirements and backlog priorities, and delivering technical ...

stories, acceptance criteria, and prioritized backlog items across the AIOps product lifecycle. Ownership of high-impact AIOps capabilities, including noise reduction, event management, correlation, anomaly detection, root cause analysis, predictive alerting, and self-healing remediation. Partner across Operations, infrastructure, SRE, platform engineering, service management, application teams, security … experience in product management, IT operations, SRE, observability, platform engineering, or related enterprise technology roles. Strong understanding of AIOps concepts, including event correlation, anomaly detection, root cause analysis, noise reduction, predictive analytics, and automated remediation. Experience defining product roadmaps, managing requirements and backlog priorities, and delivering technical ...

stories, acceptance criteria, and prioritized backlog items across the AIOps product lifecycle. Ownership of high-impact AIOps capabilities, including noise reduction, event management, correlation, anomaly detection, root cause analysis, predictive alerting, and self-healing remediation. Partner across Operations, infrastructure, SRE, platform engineering, service management, application teams, security … experience in product management, IT operations, SRE, observability, platform engineering, or related enterprise technology roles. Strong understanding of AIOps concepts, including event correlation, anomaly detection, root cause analysis, noise reduction, predictive analytics, and automated remediation. Experience defining product roadmaps, managing requirements and backlog priorities, and delivering technical ...

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 ...

business objectives, including sustainability and operational efficiency.Develop and deploy predictive and prescriptive models for key use cases such as demand forecasting, optimisation, and anomaly detection in infrastructure projects.Establish best practices for model lifecycle management, including MLOps, monitoring, and retraining, ensuring alignment with AECOM’s global standards.Extract actionable … AECOM’s global projects.Analyse real-time sensor and telematics data to enable predictive maintenance and operational efficiency for connected assets in infrastructure projects.Implement anomaly detection and streaming inference solutions to improve asset performance and reduce downtime.Mentor junior data scientists and analysts, fostering a culture of innovation ...

with engineers, analysts, and commercial stakeholders, you will translate ambiguous business problems into precise technical solutions and bring novel approaches such as graph networks, anomaly detection, and behavioural signals into production where they create real impact. Who you are End-to-end ML ownership across the full … systems in early-stage startups or small greenfield teams. This is a strong positive signal. Hands-on production experience with graph neural networks, anomaly detection, or behavioural biometrics, beyond prototyping or fine-tuning. Familiarity with AWS (SageMaker, Lambda, S3, Athena) and CI/CD practices. Experience mentoring ...

fraud interventions, balancing customer experience against loss reduction. Size fraud typologies across our product lines to inform prioritization and investment decisions. Build and maintain anomaly detection systems to surface novel fraud vectors before they scale. Work closely with fraud operations, engineers, product managers, and data analysts … technical findings clearly to non-technical stakeholders and translate insights into action. What Success Looks Like in This Role: Production-grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale. Well-designed experiments that successfully balance customer experience against ...

building practical tools to identify and resolve issues before they reach customers. The Role You will: Design and develop data quality checks covering validation, anomaly detection, freshness and coverage. Own and improve production web-scraping infrastructure, including Playwright, proxies and anti-bot handling. Build and maintain data … ship solutions efficiently. About You Strong Python and SQL skills, with hands-on dbt and BigQuery experience. Proven experience designing data quality, validation and anomaly detection processes. Production experience with web scraping at scale, ideally using Playwright or an equivalent. Experience with big data sets ...

resolution Encode triage logic into automation pipelines so future instances are classified and escalated without manual intervention Apply ML and AI techniques — crash clustering, anomaly detection, pattern recognition — to build smarter triage pipelines Build debug tooling, scripts, and CI/CD integrations that surface OS-level signals … Exposure to automation frameworks, CI/CD pipelines, or scalable test systems Experience applying ML or AI techniques to systems problems — crash clustering, log anomaly detection, failure classification, or intelligent alert prioritization Familiarity with LLMs or generative AI tooling in an engineering context — prompt engineering, RAG pipelines ...

strategic program design with hands-on execution, requiring you to define the operating model, build and lead a new team, and implement monitoring and anomaly detection processes that provide meaningful oversight across complex engagement work. The position requires strong leadership, structured problem-solving, and the ability … monitoring quality, increase coverage, and reduce manual effort. Partner with IT, Risk Product Portfolio agile teals to translate emerging technology capabilities – including generative AI, anomaly detection, and workflow automation – into practical program enhancements Define and own the technology roadmap for the monitoring & oversight unit , ensuring tooling ...

translating findings into practical actions. Using your expertise, you’ll design and deploy AI-driven security capabilities such as threat detection, anomaly detection and incident response. You’ll also advise on risk, compliance and regulation, ensuring we continue to meet industry standards as AI technologies ...

translating findings into practical actions. Using your expertise, you’ll design and deploy AI-driven security capabilities such as threat detection, anomaly detection and incident response. You’ll also advise on risk, compliance and regulation, ensuring we continue to meet industry standards as AI technologies ...

translating findings into practical actions. Using your expertise, you’ll design and deploy AI-driven security capabilities such as threat detection, anomaly detection and incident response. You’ll also advise on risk, compliance and regulation, ensuring we continue to meet industry standards as AI technologies ...

role has two halves that make each other work. You will build automated evaluation: model-assisted and LLM-based screening, agreement analysis at scale, anomaly and drift detection across annotation output. And you will build and run a dedicated audit team of around ten specialists in India … Build automated dataset quality evaluation and root-cause detection — model-assisted and LLM-as-judge screening, agreement analysis at scale, anomaly and drift detection across annotation output Hire, train, calibrate and manage a dedicated audit team of around ten specialists based in our India operation ...

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 ...

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 ...

known failure patterns, reducing human intervention and on-call burden by 50%+ Build comprehensive observability stacks (metrics, logs, traces) with ML-driven anomaly detection and AIOps capabilities Lead automated incident management: detection, triage, escalation, remediation, and post-incident review automation Drive DB automation: automated ...

through licence optimisation, hardware rightsizing, capacity rebalancing, decommissioning, and vendor renegotiationCost Governance Gaps — Assess and strengthen cost governance processes including approval workflows, budget controls, anomaly detection, and policy enforcementData Normalisation — Normalise cost data from disparate sources into a unified cost model, enabling consistent reporting across business units … months) based on value and feasibilityReporting & Dashboards — Design and recommend live/near-real-time cost dashboards with drill-down capabilities, trend analysis, anomaly alerts, and executive reporting viewsFINOPS PERSONA COLLABORATIONAs defined by FinOps.org, this role works with all key FinOps personas:Executives (CTO, CFO, CIO) — Present cost visibility ...

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 ...

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 ...

roadmap for 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.Own ...

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. ...

known failure patterns, reducing human intervention and on-call burden by 50%+• Build comprehensive observability stacks (metrics, logs, traces) with ML-driven anomaly detection and AIOps capabilities• Lead automated incident management: detection, triage, escalation, remediation, and post-incident review automation• Drive DB automation: automated ...

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/ ...