1 to 25 of 175 Anomaly Detection Jobs in the UK

About the Role Grade Level (for internal use): 11. The AIOps team is responsible for modernizing IT operations through intelligent observability, event correlation, anomaly detection, predictive insights, and automation. They partner with AIOps vendors, IT Operations, infrastructure, platform engineering, SRE, service management, and application teams to reduce … events, and topology data to improve visibility across cloud, on‐premises, and hybrid environments. Implement AIOps use cases, including noise reduction, event deduplication, correlation, anomaly detection, root cause analysis, and predictive alerting. Partner with engineering teams to build automated remediation and self‐healing workflows integrated with observability ...

purpose analytical methods and independent oversight-support tools tailored to regulated R&D activities. These may include statistical monitoring, predictive risk models, anomaly-detection methods, patient-safety and adverse-event reporting analytics, data-informed audit packages, risk indicators, dashboards, automated monitoring, natural-language tools, and other scalable … structured and unstructured data, data mapping, data cleaning, reconciliation, transformation, data modeling, automated quality checks, and data pipelines.Experience applying statistical analysis, central statistical monitoring, anomaly detection, forecasting, predictive modeling, machine learning, natural-language processing, generative AI, or related methods to practical clinical, safety, research, or quality problems.Ability ...

domains.* Develop KPI engineering models for network performance, service quality, fault behaviour, customer impact, capacity, and resilience.* Build statistical and machine learning models for anomaly detection, fault prediction, root-cause analysis, degradation detection, and proactive assurance.* Develop data aggregation, cleansing, enrichment, and feature engineering pipelines … topology, or service assurance data.* Understanding of telecom network domains including RAN, Core, IP/MPLS, SD-WAN, Transport, Cloud, or OSS.* Experience developing anomaly detection, fault analysis, predictive analytics, or KPI models.* Experience with data aggregation, cleansing, enrichment, and data quality assessment.* Experience with graph analytics ...

engineering role, responsible for defining the AI/ML roadmap for Enterprise Solutions while also building high-rigor analytical and predictive models for anomaly detection, variance analysis, drift detection, market and behavioral signals, forecasting, and prediction.The expectation is production-grade models, comparable in rigor … Experience combining statistical models, ML, semantic models, and rules-based logic where needed to achieve accuracy, stability, and explainability. Strong focus on data quality, anomaly detection, and monitoring, including metrics that surfacereal issuesand drive sustained improvement. Experience & Mindset 25+ years working with analytics, data science ...

engineering role, responsible for defining the AI/ML roadmap for Enterprise Solutions while also building high-rigor analytical and predictive models for anomaly detection, variance analysis, drift detection, market and behavioral signals, forecasting, and prediction. The expectation is production-grade models, comparable in rigor … Experience combining statistical models, ML, semantic models, and rules-based logic where needed to achieve accuracy, stability, and explainability. Strong focus on data quality, anomaly detection, and monitoring, including metrics that surface real issues and drive sustained improvement. Experience & Mindset25+ years working with analytics, data science ...

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 ...

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 ...

aerial systems Apply machine learning, data science, and RF-aware analytical techniques to electromagnetic, problem sets, including spectrum classification, emitter detection, anomaly detection and signal characterisation Explore and develop modern approaches for electromagnetic sensing and exploitation, including convolutional neural networks, transformers, autoencoders, graph-based methods ...

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 ...

opportunities to embed automation and AI-driven solutions into production workflows, reducing manual intervention and improving operational resilience Leverage AI-driven tools such as anomaly detection, AI-assisted log analysis, and LLM-based copilots to proactively identify production issues and accelerate triage Represent the team confidently … Proficiency in SQL and Excel; working knowledge of Python or scripting preferred Practical exposure to AI-enabled tools such as generative AI copilots and anomaly detection systems, with demonstrated ability to apply them to operational problems Strong communication skills and the confidence to represent the team ...

versus standing access, and risk-gated credential issuance (e.g. a short-lived token issued against a CrowdStrike-style risk score). Behavioural baselining/anomaly detection for workloads — defining “normal” for a recurring workflow and catching deviation at volume. SIEM integration and action attribution: distinguishing an agent … onboarding standard (e.g. mandatory MCP interfaces) and win adoption through better defaults and developer experience, not mandate alone. Design SIEM integration, behavioural baselining, and anomaly detection for agentic workflows, and centralise siloed audit logs to satisfy both security and regulatory requirements. Take bounded beachheads (for example, authenticate ...

goes next, what we retire, and what we keep. Treat the network as a system that learns. Drive the use of AI in operations: anomaly detection across flow and streaming telemetry, predictive failure analysis on optical and routing layers, automated triage and runbook execution, traffic‐engineering … billing integrations. Enough to debug jointly with the Systems team, not to own the stack. Exposure to applying ML or AI in network operations (anomaly detection on telemetry, predictive failure analysis, automated remediation, model‐informed traffic engineering). We're not looking for a researcher ...

conversational interfaces, AI-powered agents, and developer experience tools. Your scope covers everything from in-chat interactions and agent-driven workflows to proactive notifications, anomaly detection, and human-in-the-loop interventions across payroll, HR, and compliance.This isn’t just about making AI features look good … Akai, conversational interfaces, agents, labs, and developer experience tools.Establish the strategic approach for how intelligence surfaces across the platform—from proactive agent notifications and anomaly detection to in-chat actions and workflow automation.Shape strategic conversations using insights, narratives, and design vision to influence direction and uncover ...

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 ...

CrewAI). Experience with cloud platforms (AWS, Azure, GCP) or ML platforms (e.g., Databricks). Exposure to fraud detection, anti‐money laundering, anomaly detection, or graph/network‐based modelling. Understanding of model risk management, governance, and regulatory controls in financial services. ...

functionality, scalability, and efficiency of our Workday product suite. You will focus on cutting edge innovations, such as predictive analytics for workforce planning, anomaly detection in financial processes, and intelligent automation for Workday applications. You will collaborate closely with customers, mentor your team, and provide thought leadership ...

functionality, scalability, and efficiency of our Workday product suite. You will focus on cutting edge innovations, such as predictive analytics for workforce planning, anomaly detection in financial processes, and intelligent automation for Workday applications. You will collaborate closely with customers, mentor your team, and provide thought leadership ...

data observability as a first-class platform capability, leveraging modern observability tooling (for example, Monte Carlo) for automated freshness, volume, schema, and quality monitoring, anomaly detection, and end-to-end lineage so issues are detected and resolved before they reach consumers, with clear ownership and SLAs across ...

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 ...

future of cybersecurity starts with you.About the Role:CrowdStrike Services is seeking a Platform Professional Services Sr. Consultant specialised in AI for Detection and Response who would be responsible for the planning, deployment, implementation, and operational support of the CrowdStrike platform’s AI capabilities. This role will focus … assignment work existsBonus Points:Endpoint Security: Falcon platform (preferred), AV, and EDR solutionsAI/ML Technologies: Experience with machine learning models, natural language processing, anomaly detection, writing promptsProgramming for AI: Python, R, or similar languages for data analysis and model development, working with agents and/ ...

Product, Vendors, and other stakeholders. We’d love to see: Bloomberg Terminal, BQL, Enterprise, or Bloomberg data workflow experience. Experience productionizing AI, machine learning, anomaly detection, NLP, classification, or LLM‐assisted workflows. Experience with cloud platforms, CI/CD, automated testing, version control, metadata management, lineage ...