1 to 25 of 53 Anomaly Detection Jobs in the UK excluding London

forward investment in AI-driven operations. Over the course of the first year, the organization intends to incorporate AIOps and ML-assisted observability — anomaly detection, intelligent alert correlation, LLM-assisted runbook generation — into how we monitor and respond to our platform. You will be the technical owner … equivalent). Validate that what we think is resilient actually is. AI-driven operations Architect Omnicell's AIOps direction: evaluate and introduce ML-based anomaly detection, predictive alerting, automated root cause analysis, and LLM-assisted runbook or triage pipelines. Make informed build-versus-buy calls across ...

Collaborate with engineering and business stakeholders to identify performance trends, operational opportunities, and actionable insights. Create data pipelines and workflows that support operational monitoring, anomaly detection, service analytics, and business intelligence initiatives. Integrate data from multiple enterprise systems including Azure, SQL databases, APIs, cloud platforms, and operational … Azure Data Factory, Synapse Analytics, Data Lake, or related cloud data technologies. Experience creating executive dashboards and operational reporting solutions. Knowledge of machine learning, anomaly detection, predictive analytics, or statistical analysis techniques. Experience working with large-scale telemetry, operational, or IoT datasets. Familiarity with DevOps practices ...

schema design and data storage, transformation/ETL, model training and evaluation, and operational delivery. Develop statistical and machine learning models for entity resolution, anomaly detection, classification, clustering, and pattern-of-life analysis across multi-INT datasets. Build dashboards and lightweight applications that communicate key insights, assessments … schema design and data storage, transformation/ETL, model training and evaluation, and operational delivery. Develop statistical and machine learning models for entity resolution, anomaly detection, classification, clustering, and pattern-of-life analysis across multi-INT datasets. Build dashboards and lightweight applications that communicate key insights, assessments ...

such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. … such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. ...

Bristol, Warwick and LSE with industry partners. The role encompasses methodological, theoretical and computational research across institutions to deliver advances in statistical science for anomaly detection in streaming data. This is a full-time postdoctoral position of two years, with flexibility for part-time arrangements ...

machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack — from data ...

approaches, and land insight in a way that drives action. Apply machine learning, analytics and reporting 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 ...

platform is adaptable to evolving global compliance standards. AI & Automation Integration:Apply knowledge of AI/ML concepts to explore and implement intelligent automation, anomaly detection, or data classification solutions within the regulatory reporting pipelines. Hands-On Development: Write clean, robust, and testable code using Java ...

deploying machine learning models for risk scoring, compliance prediction, churn analysis and contractor performance analytics Building and deploying LLM-based solutions for text analytics, anomaly detection and automated compliance checks Working with Engineering and Product teams to integrate models into production environments across AWS and Azure Using ...

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 ...

vector stores, RAG, embeddings, tool surfaces. Python for data pipeline scripting and orchestration. Exposure to real-time analytics use cases - dashboards, alerting, and anomaly detection. Join TRG Screen and unlock your potential in an environment where innovation thrives, opportunities abound, and your contributions make a difference. ...

Automated fault detection, Root cause analysis, Dynamic RF optimisation, Automated channel selection, Automated power adjustments, Client steering, Service assurance automation, Network anomaly detection Experience leveraging machine learning and analytics to improve user experience, wireless performance, service availability and operational resilience. Ability to define architectures that ...

intelligent automation capabilities to reduce manual effort, improve operational efficiency, and enhance incident response workflows. Experience applying AI and automation solutions for alert correlation, anomaly detection, predictive monitoring, and service optimisation. Strong understanding of Site Reliability Engineering (SRE) principles, including service health, reliability, availability, observability, incident reduction ...

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 ...

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 ...

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 ...

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. ...

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. ...

emerging risks, influencing product strategy, and serving as the subject matter expert for the SecOps and Vulnerability Management strategy as well as embedding detection and response capabilities on a modern technology stack. You will collaborate globally, supporting audit, regulatory, and risk initiatives, with a focus on cloud computing … resiliency, and auditability expectations. Preferred Qualifications, Capabilities, and Skills: Experience deploying AI-native capabilities within Google SecOps, leveraging Gemini-powered intelligence and ML-based anomaly detection to enhance UEBA and accelerate SOC triage at scale. Experience partnering with Red/Purple Teams to simulate attacks and actively ...

governance and design documentation. Develop data quality frameworks, governance policies, schemas and metadata repositories. Integrate AI and machine learning into data solutions, including automation, anomaly detection and predictive data quality. Support data visualisation and translate complex data into actionable insights. Prototype and assess new architecture methods, tools ...

operational efficiency. Design and implement observability platforms to effectively monitor system health, performance, and reliability. Develop strategies for AI-driven alerting and proactive anomaly detection to reduce Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR). Establish and enforce SRE best practices, including Service ...

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 ...