19 of 19 Anomaly Detection Jobs in the North of England

forward investment in AI-driven operations. Over the course of the first year, the organization intends to incorporate AIOps and ML-assisted observability — anomaly detection, intelligent alert correlation, LLM-assisted runbook generation — into how we monitor and respond to our platform. You will be the technical owner … equivalent). Validate that what we think is resilient actually is. AI-driven operations Architect Omnicell's AIOps direction: evaluate and introduce ML-based anomaly detection, predictive alerting, automated root cause analysis, and LLM-assisted runbook or triage pipelines. Make informed build-versus-buy calls across ...

toxic combinations, identity exposure, control gaps, and vulnerability prioritization. • Build and evaluate graph algorithms and ML models including centrality, community detection, similarity, anomaly detection, node classification, link prediction, embeddings, and Graph Neural Networks. • Design GraphRAG and knowledge-grounded security assistants that combine graph traversal, vector … ArangoDB, or JanusGraph. • Graph data science: Neo4j Graph Data Science, NetworkX, PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. • Programming and engineering: Advanced Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/ ...

toxic combinations, identity exposure, control gaps, and vulnerability prioritization. Build and evaluate graph algorithms and ML models including centrality, community detection, similarity, anomaly detection, node classification, link prediction, embeddings, and Graph Neural Networks. Design GraphRAG and knowledge-grounded security assistants that combine graph traversal, vector … JanusGraph . Graph data science: Neo4j Graph Data Science, NetworkX , PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. Programming and engineering: Advanced Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers ...

should expect to join customers periodically and for technical discussions. Engineers who never meet the customer build the wrong thing. KEY RESPONSIBILITIES Take our anomaly detection work from proof of concept into production across the estate, moving from retrospective analysis to live early warning. Build the validation … stack. Hands‐on experience with time‐series, sensor or telemetry data at scale, including the realities of gaps, drift, flatlines and misbehaving devices. Applied anomaly detection or predictive modelling taken into production, with the judgement to keep methods robust and explainable rather than elaborate. Practical experience building ...

libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

prototype, and evaluate ML/AI techniques to support efficient, reliable observatory operations in areas such as observation scheduling, telescope and data quality monitoring, anomaly and RFI detection, and support for our user community. The successful candidate will be highly skilled in communication, as well … work both independently and collaboratively within a globally distributed team. Desirable Knowledge, Skills and Experience Experience applying ML/AI to time-series, imaging, anomaly detection, classification or optimisation problems. Familiarity with radio interferometric data and processing (e.g. visibilities, calibration, RFI flagging), or a willingness to learn ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

vaulting, and distributed secrets via external‐secrets patterns (e.g., AWS Secrets Manager, Azure Key Vault). Apply AI‐assisted tooling and analytics to improve anomaly detection, provisioning accuracy, and audit evidence of quality, while maintaining governance and data‐protection standards. Collaborate with engineering, operations, compliance, and security ...

applied within service management to improve operational efficiency, employee experience and service outcomes.* Awareness of modern AIOps and observability capabilities, including monitoring, event correlation, anomaly detection, intelligent alerting, operational analytics and automation.* Familiarity with enterprise service management platforms such as ServiceNow, Jira Service Management, Freshworks or similar ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

optimisation initiatives by helping analyse resource utilisation, configuration efficiency, tagging hygiene, and commitment strategies. Advanced Analytics Support: Assist in producing usage trend analysis, anomaly detection, forecasting support, and cost modelling for customer accounts. Reporting & Dashboards: Prepare and maintain financial reports, dashboards, optimisation summaries, and KPI metrics ...

large remit, and we expect AI-assisted development to be embedded in how we work Apply AI tools to accelerate pipeline development, automated testing, anomaly detection and data quality monitoring Stay current with AI developments in the data engineering space and bring new approaches into the team ...

Site Reliability Engineering (SRE) maturity, embedding monitoring, observability, automated testing and structured incident response Drive adoption of automation and AI‐enabled tooling to improve anomaly detection, incident management, vulnerability management and operational efficiency Provide technical oversight of production operations, ensuring alignment between platform standards and operational support ...

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 ...

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 ...

experience with R and/or Python Solid understanding of core methods: classification, regression, forecasting, clustering, nearest neighbour, neural networks, embeddings, dimensionality reduction and anomaly detection Strong statistical knowledge and the ability to translate complex findings for non‐technical audiences Experience delivering end‐to‐end data science ...

Postdoctoral Researcher to advance ML/AI methods for operational science. You will prototype ML/AI solutions for observation scheduling, data quality, anomaly detection, and user support, within a globally distributed team. The role requires a PhD (or near submission) in relevant fields and strong communication ...