4 of 4 Permanent Anomaly Detection Jobs in Scotland

thresholds and SLA-led alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support analytics-led monitoring for anomaly detection and predictive fault identification where relevant. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational … VLANs and optical or fibre environments. Familiarity with dashboarding, alert tuning, service health monitoring and operational reporting. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Scripting or automation experience, such as Python or Bash, would be advantageous. Comfortable working ...

lookups, event types, tags, and field extractions. · Integrate ITSI and Splunk Cloud with CMDB/ITSM systems, webhook automation, and AIOps/ML-based anomaly detection frameworks. · Troubleshoot slow or high-latency searches, identify bottlenecks, and implement best-practice SPL optimization. · Develop, optimize, and maintain advanced … proficiency in SPL, search optimization, and dashboard development. · Deep experience with ITSI, including service modelling, KPIs, thresholds, NEAP, and Service Analyzer. · Experience with MLTK, anomaly detection, forecasting, and operationalizing ML models. · Strong understanding of observability concepts (logs, metrics, traces, golden signals). · Hands-on experience with data ...

Scale Up Consultancy, is building the execution layer of an agentic decisioning powered by specialised predictive agents: → Demand forecasting → Churn modelling → Propensity scoring → Anomaly detection What makes this different Your models won’t sit in isolation. They’ll live inside agentic workflows where they must be: Explainable … engineering at scale Embedding ML into agent-based systems Core stack Python · scikit-learn · MLflow · SQL · Docker · Feature Stores Nice to have Explainable AI · Anomaly Detection · LLM/NLP integration · Real-time inference ...

performance, scalability, and high-volume data ingestion.The platform receives telemetry from environmental sensors (including infrared and visual monitoring devices) deployed across critical infrastructure sites. Anomaly detection triggers high-volume data transmission to the platform, which is used to generate actionable condition reports for customers — for example, identifying ...