25 of 25 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

technology teams to optimise semantic models for AI readiness. Apply data science, machine learning, NLP, and advanced analytics techniques to enhance insight generation and anomaly detection. Contribute to the organisation's long-term Data & AI strategy, influencing senior stakeholders and executive leadership. Establish best practices, standards, and governance frameworks ...

processes 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 GDPR compliance … stakeholder management skills; you can bridge technical depth with operational impact.Bonus PointsExperience 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 ...

/Service/Marketing Cloud, integrations, or Apex best practices). Experience applying AI/ML in engineering workflows (e.g., coding assistants, test generation, anomaly detection, intelligent routing) or product features. Background in leading distributed teams and large‐scale refactoring or platform modernisation initiatives. Key Behaviours & Attributes ...

pipelines, including data extraction, transformation, normalisation and quality controls to support scalable AI‐enabled process discovery.Direct the application of ML techniques (clustering, sequence modelling, anomaly detection) to identify automation candidates, bottlenecks, and root‐cause patterns.Shape intelligent automation pathways, working with engineering teams to embed ML‐supported decision … logic into workflow engines, RPA bots, agentic AI and orchestration platforms.Define technical governance and model controls, including monitoring, drift detection, explainability requirements, and compliance frameworks across discovery and automation models.Facilitate workshops and training sessions to build client capabilities in data & AI literacy and process analytics.Your ideas matter. ...

detection, incident response, and vulnerability management end‐to‐end Monitor, triage, and respond to security events across the environment, including log analysis, anomaly detection, and threat hunting, with a strong awareness of modern and AI‐enabled attack vectors Own and drive security hardening across ...

governance, audit, and regulatory reviews. Platform Improvement Evaluate the suitability of existing observability platforms and recommend improvements where required. Assess opportunities to improve automation, anomaly detection, service health monitoring, and predictive alerting. Define standards and best practices for observability across future migration phases. Stakeholder Collaboration Work closely ...

AIOps roadmap, translating complex operational needs into concrete product requirements and backlog items. You will lead high-impact capabilities like noise reduction, event management, anomaly detection, and proactive remediation, partnering across IT Ops, SRE, and security to scale adoption. You will define success metrics for alert quality ...

Monitor and evaluate emerging IAM trends (e.g., passwordless authentication, decentralised identity, adaptive access controls). - Lead automation and governance initiatives, including machine-learning-based anomaly detection. - Integrate and optimise multi-factor authentication, biometrics, and mobile identity capabilities. - Drive adoption of identity threat detection and response (ITDR) solutions. ...