1 to 25 of 39 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 ...

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 ...

learning models and inference systems using complex sensor and telemetry data. Analyse multivariate time-series datasets to identify behavioural patterns and operational insights. Build anomaly detection and behavioural baselining models. Translate raw telemetry streams into meaningful, actionable intelligence. Work with streaming and low-latency data architectures … data and signal processing. Experience analysing telemetry, sensor, wearable, physiological or similar real-world datasets. Strong understanding of multivariate time-series modelling. Experience developing anomaly detection and behavioural baselining solutions. Ability to take machine learning solutions from research and experimentation into production environments. Experience solving complex problems ...

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 ...

/ELT pipelines, microservices and service mesh topologies. Champion AI, ML and agentic automation opportunities within the trading technology estate including intelligent scheduling, anomaly detection, automated P&L attribution, predictive maintenance and agentic workflow orchestration (e.g., AWS AgentCore). Define and govern DevOps, platform engineering and observability ...

/ELT pipelines, microservices and service mesh topologies. Champion AI, ML and agentic automation opportunities within the trading technology estate including intelligent scheduling, anomaly detection, automated P&L attribution, predictive maintenance and agentic workflow orchestration (e.g., AWS AgentCore). Define and govern DevOps, platform engineering and observability ...

skills necessary for the role. 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 ...

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 ...

analytics, model risk governance, and regulatory expectations for pricing/risk models. Hands‐on ML/AI for quant finance (signal extraction, surrogate modelling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimisation, hedging algorithms, execution analytics, and transaction cost modelling. Familiarity with distributed ...

revenue forecasting, sales planning, or commercial operations analytics. Hands-on experience with Generative AI frameworks such as LangChain, LlamaIndex, and similar ecosystems. Experience with anomaly detection, experimentation, and causal inference techniques. Familiarity with distributed systems technologies such as RabbitMQ, Redis, Valkey, and event-driven architectures. Knowledge ...

preventative controls. Drive adoption of automation-first principles, reducing dependency on human-driven processes. Contribute to AI-driven operational use cases, including event correlation, anomaly detection, noise reduction, operational insights, and automated remediation. Ensure AIOps capabilities are grounded in reliable telemetry, clear control boundaries, and measurable operational … Operational Excellence Define standards for telemetry, monitoring, alerting, and operational visibility across all critical systems. Ensure services are observable, measurable, and support proactive detection of issues. Improve operational readiness, incident response effectiveness, and time-to-recovery through engineering solutions. CI/CD & Platform Integration Contribute to the design ...

consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI‐assisted data tooling (AI‐powered cataloguing, natural language querying, automated data quality) where ...

Automate connectivity services (VLAN, DNS, Firewall, DDI) integrated with ServiceNow and ITSM workflows. Drive AI/ML use cases such as WAN capacity forecasting, anomaly detection, predictive analytics, and self-healing networks. Integrate and manage observability platforms (SolarWinds Orion, Elastic, Grafana, ZDX) for proactive monitoring and insights. ...

Automate connectivity services (VLAN, DNS, Firewall, DDI) integrated with ServiceNow and ITSM workflows. Drive AI/ML use cases such as WAN capacity forecasting, anomaly detection, predictive analytics, and self-healing networks. Integrate and manage observability platforms (SolarWinds Orion, Elastic, Grafana, ZDX) for proactive monitoring and insights. ...

Lambda, Aurora, Airflow, Terraform). Ensure data availability, integrity, and performance as the platform scales globally. Drive best practices in data quality, automated testing, anomaly detection, and CI/CD. Partner with Product, Engineering, and Commercial teams to translate data needs into platform capabilities. EHR Integration ...

feedback, surfacing systemic issues, and influencing platform enhancements via the Services Observability Forum.* Stay current with observability trends, including AI/ML-driven insights, anomaly detection, and emerging OSS practices, and assess their applicability.* Maintain strong knowledge of observability platform features and vendor offerings to advise teams ...

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 ...

Data, Bloomberg Terminal, and/or enterprise financial data products Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection Past project experience using Agile/Scrum methodologies to manage complex data lifecycles If indicated, please note that years of experience ...

Data, Bloomberg Terminal, and/or enterprise financial data products Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection Past project experience using Agile/Scrum methodologies to manage complex data lifecycles Experience customizing or developing annotation interfaces using Javascript ...

Automate connectivity services (VLAN, DNS, Firewall, DDI) integrated with ServiceNow and ITSM workflows. Drive AI/ML use cases such as WAN capacity forecasting, anomaly detection, predictive analytics, and self-healing networks. Integrate and manage observability platforms (SolarWinds Orion, Elastic, Grafana, ZDX) for proactive monitoring and insights. ...

that strengthen our data foundations, ensuring our data is accurate, observable, and compliant. Your mission will be to reduce the mean time to detection and resolution of data incidents, by establishing data contracts between producers and consumers, developing robust data observability systems, and embedding governance and data protection … bridge technical depth with operational impact. Bonus Points: Experience implementing automated compliance monitoring or policy-as-code systems. Familiarity with real-time anomaly detection for data pipelines. Experience contributing to or leading cross-functional data reliability initiatives. Prior experience in consumer or marketplace platforms. Passion for data ...

languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation. Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation). Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks. Professional certifications such as EnCE, GASF ...

languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation.* Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation).* Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks.* Professional certifications such as EnCE, GASF ...

management, BI, CDP/CRM, ad platforms, experimentation, consent/privacy, data warehouses) including build vs buy vs partner recommendations. Build proactive insight systems: anomaly detection, opportunity surfacing, segmentation, attribution-informed signals, and next best actions that guide teams to outcomes. Ensure Analytics actively powers other pillars ...

Code (IaC) is the organisational default and challenge inefficient legacy processes. FinOps & Governance: Enforce strict automated security and cost controls, real‐time cost‐anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches. Internal Platform ...