51 to 75 of 169 Anomaly Detection Jobs in the UK

identify opportunities for analysis, modelling or product use. Develop, compare and validate appropriate statistical and machine-learning models for classification, ranking, recommendation, forecasting, anomaly detection, similarity or extraction problems. Use NLP, embeddings and LLM-assisted techniques responsibly for classification, entity resolution, information extraction, clustering and relationship discovery ...

other motorsports series. Our software combines many capabilities, including data capture, visualisation and modelling of real time and historic data for detailed analysis, reporting, anomaly detection and enabling the best strategic decisions to be made. Through clean and consistent coding, you will contribute to optimise our methods ...

incident, backup, resilience and monitoring controls. Practical experience applying AI, Agentic AI, AIOps or intelligent automation to operational use cases such as incident triage, anomaly detection, runbook automation, knowledge search, root cause support or service desk workflows. Knowledge of observability and reliability practices, including SRE principles, service ...

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 ...

Dynamics) Exposure to fraud detection, financial crime analytics, or compliance monitoring Experience applying statistical and advanced analytical techniques (e.g., hypothesis testing, regression, anomaly detection, or machine learning) Experience working with version control systems (e.g., Git) and structured development environments (e.g., VS Code or similar), with ...

scope spans a wide variety of problems in computational advertising including brand safety classification, content suitability scoring, risk hunting and proactive threat detection, viewability prediction, Made-for-Advertising (MFA) detection, malvertising identification, and privacy-preserving measurement and integration. We are looking for an exceptional Principal Applied … production scale Experience in computational advertising, ad tech, content moderation, trust & safety, or fraud/abuse detection Expertise in adversarial machine learning, anomaly detection, or security-oriented ML applications Familiarity with industry standards: MRC accreditation, TAG certification, brand safety frameworks, IAB content taxonomy Experience with ...

with Apache Airflow. Strong working knowledge of both supervised and unsupervised techniques, including tree-based and kernel methods (gradient boosting, random forest, SVM) and anomaly-detection approaches such as Isolation Forest, Local Outlier Factor, and locality-sensitive hashing. Solid grounding in data pre-processing, feature engineering, model ...

ownership and exposure to cutting-edge technologies. The Role Build scalable data pipelines using Microsoft Fabric and Databricks Develop machine learning solutions across forecasting, anomaly detection, recommendation systems, and information extraction Work with structured, semi-structured, and document-heavy datasets Create reusable data assets and analytical products ...

across data initiatives. Develop data quality, governance, metadata and data management frameworks. Explore how AI and Machine Learning can enhance data solutions through automation, anomaly detection and predictive data quality. Translate complex technical concepts and data insights into clear recommendations for senior stakeholders. Contribute to the development ...

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 ...

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

scale data platforms. Experience in Broadband, Video, Set-Top Box, embedded devices, networking, RDK, Wi-Fi, or DOCSIS environments. Experience building telemetry-driven diagnostics, anomaly detection, root-cause analysis, observability, or intelligent troubleshooting solutions. Experience optimizing AI/LLM applications for accuracy, reliability, latency, scalability, and cost. ...

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 ...

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 ...

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 ...

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 ...

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 ...

measure platform KPIs including ingestion reliability, data quality, latency, availability, scalability, platform adoption, and cost efficiency. Drive AI‐enabled observability initiatives leveraging telemetry intelligence, anomaly detection, root cause analytics, automation, and operational insights. Manage vendor relationships and technical partnerships across observability, analytics, security, and cloud platform ecosystems. ...

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 technologies.Experience contributing ...

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. ...

team. Job Responsibilities: Develop and implement advanced machine learning models and algorithms to address 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 ...

interested in how AI can improve analytical work. Hands-on experience using Gen AI for areas such as automated insight generation, AI-assisted analysis, anomaly detection or intelligent automation would be a strong advantage. Machine learning experience is also beneficial. Experience within Customer Success, Operations, Digital Experience ...

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 ...

regulated, financial, energy or other business‐critical technology environment. Experience applying AI‐assisted tools safely for code review, vulnerability triage, log analysis, anomaly detection, documentation, or security automation. Academic degree in cyber security, computer science, or a comparable field. Proficiency in spoken and written German. ...

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 ...