26 to 50 of 148 Anomaly Detection Jobs in England

business domains — defining, validating, and owning the definitions, metrics and models that drive decisions.Apply machine learning to real business problems: predictive modelling, classification, segmentation, anomaly detection, and forecasting.Use LLMs and generative AI to build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering ...

ecosystem. - Real-time trend monitoring and predictive analytics. - Customer intelligence, behavioural segmentations and personalisation. - Self-Service Business Intelligence. - Early warning systems, alerts and automated anomaly detection across payment journeys. The Data & AI Senior Product Owner is responsible for identifying gaps and opportunities for new data ...

ecosystem.• Real-time trend monitoring and predictive analytics.• Customer intelligence, behavioural segmentations and personalisation.• Self-Service Business Intelligence.• Early warning systems, alerts and automated anomaly detection across payment journeys.The Data & AI Senior Product Specialist is responsible for identifying gaps and opportunities for new data and AI services ...

ecosystem.• Real-time trend monitoring and predictive analytics.• Customer intelligence, behavioural segmentations and personalisation.• Self-Service Business Intelligence.• Early warning systems, alerts and automated anomaly detection across payment journeys.The Data & AI Senior Product Specialist is responsible for identifying gaps and opportunities for new data and AI services ...

business priorities.Build and optimize monitoring, observability, and alerting capabilities using tools such as Prometheus, Grafana, AppDynamics, and Splunk.Apply AIOps capabilities to improve event correlation, anomaly detection, root cause analysis, predictive insights, and proactive issue prevention.Partner with engineering, infrastructure, production support, security, and risk teams to ensure developed ...

/v4 Foundation or experience aligning QA with service management practices. Experience applying AI/ML in Quality Engineering, including test optimisation, defect prediction, anomaly detection or analytics-led assurance. Experience with enterprise orchestration tools such as Control-M, Autosys or equivalent scheduling platforms. Experience with master ...

consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI‐assisted data tooling (AI‐powered cataloguing, natural language querying, automated data quality) where ...

version control (Git), testing frameworks, and infrastructure as code (Terraform). Demonstrated ability to embed data quality, observability, and alerting into pipelines (automated validation, anomaly detection, monitoring). Experience leading technical design sessions, owning architecture decisions, and communicating trade offs clearly to both technical and non technical ...

data pipelines’ SLA and dependency management.Writing technical documentation for data solutions, and presenting at design reviewsSolving data pipeline failure events and implementing sound anomaly detection Working with various teams from analytics to product owners and front end developers on tracking solutions and solving technical challengesLeading medium ...

between regulatory intent and technical execution. In this role, you will serve as the global second-line authority and owner of financial crime detection models, risk analytics, and automated control frameworks. You will own the global methodology, thresholds, and data-scoring models used to identify and mitigate financial … native, API-first environment where transaction decisions must be executed algorithmically in milliseconds.Proven track record of moving advanced machine learning, neural networks, or behavioral anomaly detection models out of testing and into live, global compliance operations safely and transparently.Experience utilizing graph databases and link analysis to identify ...

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 ...

champion within Corporate FP&A, defining and executing the AI roadmap for planning, forecasting, reporting and process automation.Embed AI-enabled forecasting, anomaly detection, driver-based scenario modelling and natural language query capabilities into the EPM and reporting stack.Partner with the CIO, Data & AI teams and Finance leadership ...

tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root-cause analysis, anomaly detection, and semantic log clustering. Self-healing Infrastructure Engineering: Experience designing closed-loop, self-healing systems that autonomously execute recovery actions (e.g. ...

tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root‐cause analysis, anomaly detection, and semantic log clustering. Self‐Healing Infrastructure Engineering: Experience designing closed‐loop, self‐healing systems that autonomously execute recovery actions (e.g. ...

join our growing AML Team in London.This role is a unique opportunity to work behind the scenes of company transactions, develop our risk detection and assessment to the next level regarding regional typology understanding and at the same time, provide our customers with the seamless service they deserve. … capabilities.Here’s how you’ll be contributing:Innovate and Develop: Lead the development and deployment of machine learning models, including neural networks, anomaly detection, graph-based models, Transformers. Design and build modular detection systems able to detect in an evidenceable way red flags ...

Lambda, Aurora, Airflow, Terraform). Ensure data availability, integrity, and performance as the platform scales globally. Drive best practices in data quality, automated testing, anomaly detection, and CI/CD. Partner with Product, Engineering, and Commercial teams to translate data needs into platform capabilities. EHR Integration ...

Monitor adherence to risk and control guidelines for data access and use.Data quality, reliability, and lineage - Define data contracts for telemetry sources; implement validation, anomaly detection, and reconciliation; document definitions (e.g., formulas, thresholds) and end-to-end data lineage from raw signals to KPIs and insights.Automation ...

including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines. Experience with AIOps, intelligent observability, automated remediation, anomaly detection, and AI‐assisted cloud operations. Experience with cloud security, compliance, and governance frameworks, including considerations specific to AI‐enabled workloads. Google ...

MLOps, including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines.Experience with AIOps, intelligent observability, automated remediation, anomaly detection, and AI-assisted cloud operations.Experience with cloud security, compliance, and governance frameworks, including considerations specific to AI-enabled workloads.Google Cloud certifications ...

correctness are non‐negotiable Designing and enforcing data integrity frameworks across betting, trading, and customer data domains – including reconciliation between source and target systems, anomaly detection, and audit trail requirements Overseeing the implementation of regulatory and compliance reporting pipelines that meet the requirements of the UK Gambling ...

correctness are non‐negotiable Designing and enforcing data integrity frameworks across betting, trading, and customer data domains – including reconciliation between source and target systems, anomaly detection, and audit trail requirements Overseeing the implementation of regulatory and compliance reporting pipelines that meet the requirements of the UK Gambling ...

telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries, OPA policies ...

telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries, OPA policies ...

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 ...

request, model and agent error rates, retrieval quality and drift, with dashboards and alerting that surface problems before users do. FinOps: Embed cost estimation, anomaly detection and resource optimisation into the pipeline as a default rather than a monthly review. Security posture: Apply zero-trust networking, least ...