20 of 20 Permanent Anomaly Detection Jobs in England

tools like Prometheus, Grafana, ELK, and AWS CloudWatch. Build real-time dashboards to visualize system health and reliability metrics. Configure intelligent alerting based on anomaly detection and thresholds. Combine metrics, logs, and traces to enable root cause analysis and reduce Mean Time to Resolution (MTTR). Knowledge … AIOps or ML-based anomaly detection for proactive reliability management. Collaboration Work closely with development teams to integrate reliability into application design and deployment Promote a culture of shared responsibility for uptime and performance across engineering teams. Qualifications Deep expertise with various AWS services. Advanced knowledge ...

Role We are seeking a Data Scientist to work on advanced analytical solutions across biometric and geospatial (GPS) datasets, with a particular focus on anomaly detection. You will work with multiple complex data streams, including biometric data captured via wearable technologies and location-based datasets. This role will suit … technical direction in a fast-paced, evolving environment with minimal structure. Key Responsibilities Develop and deploy data science models, with a focus on anomaly detection Work across multiple datasets, including biometric and GPS/location data Analyse and interpret data generated from wearable hardware devices Collaborate with ...

Embedding AI into enterprise SaaS products Collaborating closely with product and engineering teams Developing and deploying AI/ML features into live products Implementing anomaly detection or predictive analytics on structured operational data Managing MLOps including deployment pipelines, model monitoring, and retraining Designing REST APIs and integrating … product roadmap Job Requirements: Experience in software engineering with a focus on AI Proven experience in production AI/ML feature development Understanding of anomaly detection or predictive analytics Proficiency in Python and TypeScript/JavaScript Experience with REST API design and MCP integration patterns Knowledge ...

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 ...

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

human identity sprawl. Ensure strong monitoring, alerting, and telemetry for IAM services and integrations, and partner with SecOps where needed (SIEM, logging, anomaly detection). Drive reduction in repeat incidents through disciplined root cause analysis, prevention, and engineering partnership. Build strong partnerships across Security, Infrastructure, HR, application ...

Design and implement automated testing frameworks to validate data pipelines and ensure compliance with aerospace standards. Develop and maintain Python scripts for data validation, anomaly detection, and quality assurance. Analyse complex datasets to identify trends, inconsistencies, and optimisation opportunities. Collaborate with engineering and IT teams to define ...

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 ...

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 ...

Build and deploy ML models across: Predictive analytics (performance trends, forecasting) Computer vision (video analysis, media enhancement) NLP (fan insights, content intelligence, knowledge systems) Anomaly detection (telemetry/operations monitoring) Build scalable inference pipelines (real-time + batch) Implement monitoring, drift detection, and retraining workflows ...

packs; track benefits realization versus plan and highlight trade‐offs. AI‐Enabled Transformation and Engineering Partnership Identify and validate AI/ML opportunities (e.g., anomaly detection, match optimization, exception triage); design‐controlled pilots and scale proven solutions. Partner with engineering to prioritize capabilities, ensure backlog quality ...

data Deep Learning NLP + LLMs, GenAI agent pipelines Simulations Graph-based models Time-series forecasting Geospatial modeling Causal inference Reinforcement learning Optimization problems Anomaly detection* **Deployment Experience*** Proven track record of deploying or partnering on **customer-facing production ML systems**.* Proficiency in Python ...

certification or formal training APM and distributed tracing experience - OpenTelemetry, Jaeger, Zipkin Kubernetes at scale Familiarity with AI/ML concepts applied to AIOps - anomaly detection, predictive alerting, topology mapping WHAT'S ON OFFER Complex, high-impact work across serious enterprise clients from day one A close ...

their outputs usable for downstream systems and training our Delivery Team for field deployment. The role spans multi-domain sensor fusion, AI-assisted analysis, anomaly detection, augmented reality, autonomous sentry operation, and evidence collection. You'll work closely with colleagues across software, hardware, data science, and infrastructure ...

also play a key role in embedding AI and automation across the testing lifecycle, from intelligent test selection and self‐healing automation through to anomaly detection and governance for AI‐powered features. What you’ll be doing Defining and delivering the enterprise quality strategy across functional, automation ...

hybrid capacity from our London office. You Will Develop and deploy AI‐native solutions to automate trading, remittance network funding, and FX cost anomaly detection. Stay ahead of the market: Monitor trends in payments, Treasury, and stablecoin, bringing an informed perspective to product planning and external partnerships. ...

. Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . Graph based ML familiarity: link prediction, anomaly detection, traversal, community detection. NLP/NLU skills: entity/relation recognition, summarisation, topic modelling, classification, coreference resolution. Visualization and communication Graph ...

whitepapers , contributing to product strategy Familiarity with security audits , RFP/RFI responses Exposure to security analytics tools and techniques, such as log analysis , anomaly detection, or traffic monitoring , with an interest in developing stronger skills Understanding of full packet capture and analysis concepts, or hands ...

development skills, experience working with real-world sensor systems, and the ability to partner effectively with AI/ML components to deliver intelligent detection, classification, and tracking capabilities. About the role of Sensor Software Engineer - (not exhaustive): You'll work on the "sensors at the fringe" fixed … downstream systems and training our Delivery Team for field deployment. The role of Sensor Software Engineer spans multi-domain sensor fusion, AI-assisted analysis, anomaly detection, augmented reality, autonomous sentry operation, and evidence collection. You'll work closely with colleagues across software, hardware, data science, and infrastructure ...