12 of 12 Permanent 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 ...

Bristol, Warwick and LSE with industry partners. The role encompasses methodological, theoretical and computational research across institutions to deliver advances in statistical science for anomaly detection in streaming data. This is a full-time postdoctoral position of two years, with flexibility for part-time arrangements ...

intelligent automation capabilities to reduce manual effort, improve operational efficiency, and enhance incident response workflows. Experience applying AI and automation solutions for alert correlation, anomaly detection, predictive monitoring, and service optimisation. Strong understanding of Site Reliability Engineering (SRE) principles, including service health, reliability, availability, observability, incident reduction ...

events publish to Pub/Sub for asynchronous workflows such as: automated identity lifecycle tasks access review event triggers logging and audit forwarding security anomaly detection Build Cloud Functions, Cloud Run microservices, or containerized services to process Pub/Sub messages. Implement robust event-processing patterns including ...

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 ...

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 ...

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 ...

defined requirements. Desirable 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 ...

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 ...

drop-off alerts. Design and implement real-time revenue monitoring dashboards tracking deposit/withdrawal volumes, payment gateway health, and transaction success rates with anomaly detection against expected baselines. Build revenue impact calculation models for use during major incidents, enabling the team to quantify business impact … including threshold tuning, correlation rules, suppression logic, and noise reduction techniques. Experience building business‐level monitoring including revenue dashboards, customer journey tracking, and transaction anomaly detection. Ability to translate technical metrics into business impact language for executive stakeholders. Strong analytical skills with experience in defining KPIs, setting baselines ...

will act as first responder to alerts, classify severity, and execute runbook procedures to restore service swiftly. The role emphasizes incident management, proactive anomaly detection, and tight collaboration with cross-functional teams during peak events. You will document triage notes, update Jira, and help tune thresholds ...