1 to 25 of 35 Remote/Hybrid Anomaly Detection Jobs in England

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 ...

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 ...

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 ...

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 ...

agent implementation. Design and implement AI-powered features within Compensation Collection, Shadow Payroll, and Equity products including intelligent data extraction from compensation statements, anomaly detection on payroll inputs, LLM-assisted user workflows, and retrieval-augmented generation (RAG) over tax and payroll guidance. Evaluate, integrate, and operationalize ...

build scalable, secure AI systems.What You'll Be DoingDesign, 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 on models before ...

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 … 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 ...

ensuring that the engineering team’s velocity is sustained by high-confidence automated processes. Lead the development of AI-augmented test strategies. Architect predictive anomaly detection systems and AI-driven test generation engines that evolve alongside our software, turning the test suite into an intelligent system that ...

ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc.Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc.Deep understanding of the GenAI landscape and agentic frameworks.Experience working in the full model lifecycle (including experimentation, training, testing, monitoring ...