1 to 25 of 44 Remote/Hybrid Anomaly Detection Jobs in the UK

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 ...

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 ...

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 ...

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/ ...

ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation … ideally genomic data. Developing models, algorithms or rule-based systems that support human decision-making, ideally where explainability, auditability and risk management are important. Anomaly detection, behavioural analytics, security monitoring or detection engineering. Risk quantification methods from fields such as actuarial science, epidemiology, operational research ...

deploying machine learning models for risk scoring, compliance prediction, churn analysis and contractor performance analytics Building and deploying LLM-based solutions for text analytics, anomaly detection and automated compliance checks Working with Engineering and Product teams to integrate models into production environments across AWS and Azure Using ...

service provisioning.Lead SAP technical architecture decisions for hybrid and cloud-native environments (RISE, hyperscalers).Drive adoption of AIOps for SAP operations (predictive monitoring, anomaly detection, auto-remediation).Implement automation for repetitive BASIS operations (system health checks, patching, job management).Leverage AI/ML tools for incident prediction ...

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 ...

tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root-cause analysis, anomaly detection, and semantic log clustering. Self-healing Infrastructure Engineering: Experience designing closed-loop, self-healing systems that autonomously execute recovery actions (e.g. ...

tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root‐cause analysis, anomaly detection, and semantic log clustering. Self‐Healing Infrastructure Engineering: Experience designing closed‐loop, self‐healing systems that autonomously execute recovery actions (e.g. ...

join our growing AML Team in London.This role is a unique opportunity to work behind the scenes of company transactions, develop our risk detection and assessment to the next level regarding regional typology understanding and at the same time, provide our customers with the seamless service they deserve. … capabilities.Here’s how you’ll be contributing:Innovate and Develop: Lead the development and deployment of machine learning models, including neural networks, anomaly detection, graph-based models, Transformers. Design and build modular detection systems able to detect in an evidenceable way red flags ...

driven decisions . Implement feedback loops to continuously improve model performance . AI-Driven SRE Enablement Develop ML/AI models for anomaly detection, incident prediction, and root cause analysis across distributed systems . Implement intelligent alerting systems to reduce noise and improve signal fidelity . Build ...

telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries, OPA policies ...

telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries, OPA policies ...

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 ...

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 ...

performance intelligence, and financial reconciliation across all travel verticals.Architect and evolve reference pricing systems leveraging predictive modeling, elasticity signals, competitive benchmarking, and real-time anomaly detection.Build the supplier intelligence layer, transforming transactional data into automated performance signals, demand insights, and pricing diagnostics.Establish and govern the canonical source of truth … framing, signal design, evaluation metrics (e.g., precision/recall tradeoffs, forecasting accuracy), monitoring frameworks, drift detection, and retraining strategies.Experience shipping predictive systems, anomaly detection platforms, automated decisioning infrastructure, or model-driven pricing systems at scale.Experience owning pricing systems, financial reporting platforms or marketplace intelligence tools.Deep ...

intelligence, and financial reconciliation across all travel verticals. Architect and evolve reference pricing systems leveraging predictive modeling, elasticity signals, competitive benchmarking, and real-time anomaly detection. Build the supplier intelligence layer , transforming transactional data into automated performance signals, demand insights, and pricing diagnostics. Establish and govern the canonical source … signal design, evaluation metrics (e.g., precision/recall tradeoffs, forecasting accuracy), monitoring frameworks, drift detection, and retraining strategies. Experience shipping predictive systems, anomaly detection platforms, automated decisioning infrastructure, or model-driven pricing systems at scale. Experience owning pricing systems, financial reporting platforms or marketplace intelligence ...

stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link prediction, anomaly detection) Optimize graph performance, scaling, and query efficiency Liaise with client stakeholders: translate business problems into graph solutions Mentor junior engineers, contribute ...

world, production problems Strong Python skills (or a similar language used in applied data science) Experience with supervised learning and unsupervised techniques such as anomaly detection Exposure to cloud‐based model training, deployment and automation A strong sense of ownership and accountability for data science outputs Experience ...

world, production problems Strong Python skills (or a similar language used in applied data science) Experience with supervised learning and unsupervised techniques such as anomaly detection Exposure to cloud‐based model training, deployment and automation A strong sense of ownership and accountability for data science outputs Experience ...

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 ...

tooling 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 ...

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 for responsible ...

deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) to customer production environments. Communicate results and trade-offs to senior stakeholders; steer roadmaps and influence product direction with evidence. Lead scoping ...