51 to 75 of 171 Anomaly Detection Jobs in England

churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning. Optimization: Building engines for marketing spend, inventory management, or resource allocation. Causal ...

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 ...

OpenTelemetry traces, change events, and runbooks to accelerate Mean Time to Detection (MTTD) and Resolution (MTTR). Safe Production Automation: Develop proactive anomaly detection and Human-in-the-Loop (HITL) remediation workflows with rigorous safety, security, and quality guardrails. Reliability & Scalability Engineering: Partner with application ...

graph and putting it to work in an enterprise. Machine learning and data science — building models that solve real business problems, such as forecasting, anomaly detection or classification. FDE, presales or innovative professional services — experience on a team that builds with customers. Technical consulting — designing and building ...

graph and putting it to work in an enterprise. Machine learning and data science — building models that solve real business problems, such as forecasting, anomaly detection or classification. Experience in our industries — manufacturing, engineering, supply chain, pharma, aerospace or financial services. Travel Some travel is expected ...

reporting tools to city and transit operators. AI/ML Readiness: Monitor and evaluate practical AI use cases (e.g., predictive maintenance for hardware, anomaly detection) to be integrated into the roadmap, value-add features once the core BI and Data Lake foundations are fully established. Data Governance ...

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 ...

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 ...

data warehouse. Familiarity with data pipelines, APIs, workflow orchestration or system integrations. Exposure to governance, risk and compliance (GRC) platforms. Experience with statistical analysis, anomaly detection, forecasting or early‐warning indicators. Experience using external regulatory, market or threat intelligence to support risk monitoring. Familiarity with AI agents ...

design it for the finance people who will use it. AI on the platform. This is where financial data turns into decisions: predictive forecasting, anomaly detection, AI-generated commentary and agentic workflows, with the human-in-the-loop controls that keep finance in charge of what ...

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. ...

before systems are decommissioned. Build or coordinate data pipelines and ETL processes; apply AI and machine learning tooling to accelerate data ingestion, deduplication, and anomaly detection. Design automated quality checks that reduce manual validation effort without compromising accuracy. Master Data Management & Governance Apply MDM principles to align acquired data ...

improvement. Job Responsibilities: Develop and implement advanced machine learning models and algorithms to solve operational challenges Deploy AI/ML solutions for process automation, anomaly detection, document intelligence, and workflow optimization Architect and oversee generative AI applications to automate and enhance business processes Build and maintain production ...

such as planning, documentation, and evidence review. Predictive Analytics & Machine Learning Experiment with ML algorithms (e.g., K-Means, Decision Trees, Isolation Forest, ARIMA) for anomaly detection, risk assessment, and forecasting. Collaborate with technical teams to integrate predictive models into audit processes. Audit Integration & Enablement Work alongside audit ...

Influence technical direction rather than simply execute a roadmap. Build solutions across the complete machine learning lifecycle. Develop expertise in cutting-edge areas including anomaly detection, agentic AI and intelligent decision-support systems. Operate in a high-trust environment with genuine ownership and accountability. Move faster, with ...

computational approaches to advance flood hazard modeling capabilities Explore, prototype, and assess artificial intelligence and machine learning methods for surrogate modeling, spatial downscaling, anomaly detection, feature extraction, emulator development, and workflow automation Develop and maintain reproducible scientific workflows, data processing pipelines, and code repositories using modern software ...

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 ...

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 finance ...

Google Cloud security best practices and IAM implementation Experience with Google Cloud data services including BigQuery and Dataflow Experience with cloud cost management (budgeting, anomaly detection, cost analysis and reporting) Experience working on a geographically distributed team across time zones Nice to have: Google Cloud Professional certifications ...

throughout the software delivery lifecycle.Familiarity with OpenTelemetry, automation, Infrastructure as Code and modern engineering practices.Knowledge of AI-powered operations (AIOps), operational intelligence, event correlation, anomaly detection, and emerging AI capabilities within operations platforms.Ability to define how Generative AI, AI assistants and intelligent operational workflows can enhance observability ...

software delivery lifecycle. Familiarity with OpenTelemetry, automation, Infrastructure as Code and modern engineering practices. Knowledge of AI-powered operations (AIOps), operational intelligence, event correlation, anomaly detection, and emerging AI capabilities within operations platforms. Ability to define how Generative AI, AI assistants and intelligent operational workflows can enhance ...

huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements ...

huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements ...

Machine Learning Design, build, and deploy machine learning models that solve complex business and operational challenges. Develop solutions across predictive analytics, computer vision, anomaly detection, and natural language processing. Create scalable inference pipelines for both real-time and batch processing workloads. Implement model monitoring, performance tracking, drift … detection, and retraining processes. Rapidly prototype new ideas and validate use cases before scaling successful solutions into production. Research emerging AI and data technologies and identify opportunities to apply them in novel ways. Data Engineering & Platforms Design and maintain robust, scalable data pipelines. Integrate diverse data sources including ...

identify scraping, bot activity and unauthorised content extraction using fingerprint analysis, behavioural signals and network data Build and maintain a portfolio of detection signals and continuously evolve them as threat actors change their tactics Measure detection performance through coverage, precision, false-positive rates and baseline benchmarking … scholarly communications Experience with modern data transformation tooling such as Dataform or dbt Experience developing classification or machine learning models for user behaviour analysis, anomaly detection or segmentation Experience measuring the impact of external platforms on traffic, engagement, discoverability and commercial outcomes ...