76 to 100 of 173 Anomaly Detection Jobs in the UK

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 ...

implement models that to deliver innovate actionable intelligence for Gravity users. Key Responsibilities Develop ML models for: Wi‐Fi performance prediction and classification Anomaly detection in home networks and CPE telemetry Root‐cause analysis for subscriber connectivity issues Optimization of channel selection, band steering, mesh/Extender ...

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 ...

foundation for finance.AI-augmented, intelligent finance. You own the design of the AI and machine-learning use cases that make planning better — predictive forecasting, anomaly detection, automated variance analysis, AI-generated commentary and agentic planning workflows among them — and the human-in-the-loop controls that keep ...

foundation for finance.AI-augmented, intelligent finance. You own the design of the AI and machine-learning use cases that make planning better — predictive forecasting, anomaly detection, automated variance analysis, AI-generated commentary and agentic planning workflows among them — and the human-in-the-loop controls that keep ...

foundation for finance.AI-augmented, intelligent finance. You own the design of the AI and machine-learning use cases that make planning better — predictive forecasting, anomaly detection, automated variance analysis, AI-generated commentary and agentic planning workflows among them — and the human-in-the-loop controls that keep ...

AIOps: Translate NFRs into pragmatic architecture decisions, define SLOs/SLIs, and design modern observability (metrics, logs, traces). Apply AIOps for alert reduction, anomaly detection, incident triage, and continuous improvement across hybrid and cloud platforms.Advisory & communication: Simplify complexity for senior audiences; align diverse viewpoints; and negotiate ...

technical demos that had to stand up in front of real users.Experience packaging desktop applications or supporting Windows-heavy enterprise environments.Exposure to forecasting, anomaly detection, optimization, time-series systems, or other decision-support workflows.Experience in energy, commodities, financial, trading, market operations, or industrial workflows.Team and environmentQuantAI sits ...

clear judgment on when AI is appropriate versus deterministic or rules-based approaches. Strong understanding of analytics and AI in production (e.g. data quality, anomaly detection, fraud/AML, workflow automation) and understands what it takes to run these reliably in regulated environments. Designs with security ...

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 ...

Design & Data Architecture Identify key signals required for: Quality & reliability Latency & throughput Cost tracking & optimisation MCP usage patterns User workflow insights Failure pattern detection Guardrail and safety event monitoring Define retention rules … considerations, anonymisation and usage policies in partnership with AI Governance and Compliance. Platform & Tooling Own requirements for dashboards, monitoring tools, model comparison views, anomaly detection alerts, and performance scorecards. Design systems that allow product and engineering teams to self-serve insights about AI model behavior ...

Snowflake connectivity configurations. Familiarity with Cloud Governance frameworks, Cost Optimization strategies, Azure Advisor, and enterprise Tagging Standards. Prior exposure to AIOps (AI-driven Operations), anomaly detection mechanisms, and proactive monitoring strategies. Professional & Soft Skills Exceptional troubleshooting capabilities and structured problem-solving skills. Polished stakeholder communication skills with ...

experience in global data operations or support roles within the financial industry, with a track record of delivering high-quality data solutions.Exposure to anomaly detection methods, statistical tools, and best practices for managing data quality workflows.Excellent communication skills, with experience collaborating across technical, investment, and senior leadership ...

backend API services, model integration, model monitoring, evaluations and deployments Engineer feature and context pipelines balancing batch and streaming patterns to feed forecasting and anomaly‐detection models, collaborating closely with data scientists to productionise algorithms. Build the data plane for evaluation , implementing rigorous frameworks to continuously monitor ...

languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation. Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation). Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks. Professional certifications such as EnCE, GASF ...

security practices, including MFA, passwordless/FIDO2, least privilege and Zero Trust. Automate and improve IAM operations, including exploring AI-enabled approaches such as anomaly detection and intelligent access-review support. Partner with Technology, Risk & Compliance and local teams to ensure consistent IAM standards across Odevo. Provide ...

languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation.* Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation).* Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks.* Professional certifications such as EnCE, GASF ...

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 ...

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 ...

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

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 ...

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 ...