17 of 17 Permanent Anomaly Detection Jobs in London

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 ...

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 ...

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 ...

chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards ...

including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines. Experience with AIOps, intelligent observability, automated remediation, anomaly detection, and AI-assisted cloud operations. Experience with cloud security, compliance, and governance frameworks, including considerations specific to AI-enabled workloads. Google ...

demos that had to stand up in front of real users. Experience packaging desktop applications or supporting Windows-heavy enterprise environments. Exposure to forecasting, anomaly detection, optimization, time-series systems, or other decision-support workflows. Experience in energy, commodities, financial, trading, market operations, or industrial workflows. Team ...

resolving complex investigations using data from multiple security technologies and information sources. Correlating security alerts and events, executing advanced queries, and applying behavioural and anomaly-detection techniques. Leveraging commercial and open-source technologies, including AI-enabled tools, to automate repetitive tasks, enhance threat detection … alignment with industry best practices and evolving AI capabilities. Recommending adjustments to security tools and processes to reduce false positives and improve detection quality. Examining and correlating log data across endpoints, databases, applications, identity systems, networks, mobile platforms, and cloud environments. Working with SOAR platforms, SIEM technologies ...

near-real-time data flows. Shape the architecture for AI-enabled Financial Crime capabilities, including alert optimisation, investigation summarisation, adverse media triage and anomaly detection. Ensure AI and data capabilities are explainable, auditable and appropriate for a highly regulated environment. Establish architecture standards across security, resilience, data lineage, model ...

work on include intelligent data extraction from unstructured and semi-structured documents, content classification and routing, cross-language translation, fraud and document-tampering detection, and workflow optimisation across business processes. You'll be trusted to turn ambiguous, often first-of-a-kind problems into dependable services that … regulatory and compliance requirements. Experience building production systems for one or more of: document/data extraction, NLP-based classification, machine translation, fraud or anomaly detection, or workflow automation. Experience evaluating the performance of Generative AI applications – exposure to Mlflow, experiment design, evaluation methodologies. Strong background ...

networks, underpinned by SON and closed-loop automation. Apply Generative AI & Autonomous Networks, identify and pilot GenAI use cases (AI-assisted planning, anomaly detection, predictive maintenance) and architect solutions aligned with TM Forum L0–L5 and ETSI ZSM frameworks. Productionise AI/ML models, collaborate with data ...

secure AI systems. What You'll Be Doing Design, develop, and deploy machine learning models for traditional ML use cases, including forecasting, classification, and anomaly detection. Build and deliver Generative AI and LLM-powered applications using modern AI frameworks. Lead experimentation cycles, defining hypotheses, running evaluations, and iterating ...

emerging risks, influencing product strategy, and serving as the subject matter expert for the SecOps and Vulnerability Management strategy as well as embedding detection and response capabilities on a modern technology stack. You will collaborate globally, supporting audit, regulatory, and risk initiatives, with a focus on cloud computing … resiliency, and auditability expectations. Preferred Qualifications, Capabilities, and Skills: Experience deploying AI-native capabilities within Google SecOps, leveraging Gemini-powered intelligence and ML-based anomaly detection to enhance UEBA and accelerate SOC triage at scale. Experience partnering with Red/Purple Teams to simulate attacks and actively ...

plans, including performing RF tuning, managing remedy incidents, and requesting network investments. AI Training: Provide feedback to data-driven AI operations algorithms to improve anomaly detection and root cause analysis recommendations. Collaboration: Work closely with operations and managed service providers to ensure performance-impacting faults are progressed ...

plans, including performing RF tuning, managing remedy incidents, and requesting network investments. AI Training: Provide feedback to data-driven AI operations algorithms to improve anomaly detection and root cause analysis recommendations. Collaboration: Work closely with operations and managed service providers to ensure performance-impacting faults are progressed ...

integration patterns, API standards, event-driven architectures and data governance frameworks. Shape AI-enabled financial crime capabilities including alert optimisation, case investigation support and anomaly detection. Establish architecture guardrails covering security, resilience, auditability, regulatory traceability and model governance. Influence vendor selection and platform strategy through architecture leadership and technical ...

Drive platform adoption across Kingfisher banners. Setup and operate platform governance that safeguard payment flows, ensure compliance, and embed robust fraud controls and detection capabilities. Line manage multiple Product Owners. Develop product practices within the product teams. Activities I do to deliver my role: Translate enterprise strategy into … ensure the platform proactively responds to emerging fraud vectors and regulatory requirements. Establish platform guardrails and adoption criteria. Ensure platform capabilities support continuous monitoring, anomaly detection, chargeback reduction, and loss prevention. Provide structured updates to senior stakeholders and governance forums. Monitor platform performance, risks, costs and scalability ...

Kubernetes-based environments. You will be at the intersection of security and engineering, developing scalable tooling, automating security controls, and enabling robust detection and response capabilities across our cloud infrastructure. In this role, you will require deep technical expertise in cloud environments, Kubernetes security, and platform automation. … Vetting (DV) UK security clearance. Preferred qualifications: Certifications in Security (e.g., GSEC, CISSP, CISM, OSCP). Experience with Kubernetes threat detection and anomaly detection. Experience with service mesh security concepts (e.g., Istio, Linkerd) and workload identity. Experience in detection engineering, logging pipeline development, or SIEM ...