1 to 25 of 169 Anomaly Detection Jobs in the UK

production deployment before a model earns trust at scale.This is a second-line position, reviewing methodologies built with scikit-learn, LightGBM, graph models, anomaly detection, and increasingly GenAI-based components. You'll also build your own tooling — agentic AI systems that read model documentation and code … with regulatory expectations on model risk, fairness, and data privacy.You'll validate emerging techniques as first-line teams adopt them — graph networks, behavioral biometrics, anomaly detection, and GenAI-based systems.You'll document validation outcomes and communicate model risks directly to first-line data scientists, ML engineers ...

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 ...

Security is a domain where AI genuinely matters. The attackers are using it, and the defenders need to as well. You'll work on anomaly detection, behavioural analysis, natural language processing for threat intelligence, and building interfaces that help analysts respond faster. The problems are adversarial … noisy, and the stakes are real. Responsibilities Build analyst-facing interfaces for investigating and responding to security threats Design and implement ML models for anomaly detection, behavioural analysis, and threat classification Create data pipelines that ingest and process security telemetry at massive scale Build APIs and backend ...

with many different collection techniques, along with internal QA tools. This role will specialise in taking our QA systems further: hardening the validation and anomaly detection that catches problems before our customers do, keeping our scrapers healthy and resilient as sources change under us, and shipping fast … puzzle and wants to own and raise an existing quality bar rather than maintain someone else's. Design and build data quality checks - validation, anomaly detection, freshness and coverage monitoring - across our core data pipelines Own and improve production web scraping infrastructure (Playwright, proxy management, anti ...

domains.* Develop KPI engineering models for network performance, service quality, fault behaviour, customer impact, capacity, and resilience.* Build statistical and machine learning models for anomaly detection, fault prediction, root-cause analysis, degradation detection, and proactive assurance.* Develop data aggregation, cleansing, enrichment, and feature engineering pipelines … topology, or service assurance data.* Understanding of telecom network domains including RAN, Core, IP/MPLS, SD-WAN, Transport, Cloud, or OSS.* Experience developing anomaly detection, fault analysis, predictive analytics, or KPI models.* Experience with data aggregation, cleansing, enrichment, and data quality assessment.* Experience with graph analytics ...

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 ...

stories, acceptance criteria, and prioritized backlog items across the AIOps product lifecycle. Ownership of high-impact AIOps capabilities, including noise reduction, event management, correlation, anomaly detection, root cause analysis, predictive alerting, and self-healing remediation. Partner across Operations, infrastructure, SRE, platform engineering, service management, application teams, security … experience in product management, IT operations, SRE, observability, platform engineering, or related enterprise technology roles. Strong understanding of AIOps concepts, including event correlation, anomaly detection, root cause analysis, noise reduction, predictive analytics, and automated remediation. Experience defining product roadmaps, managing requirements and backlog priorities, and delivering technical ...

high-quality inputs for models Designs, builds and trains data science products such as business models, predictive analytics tools, recommender systems, natural language processing, anomaly detection, forecasts, optimisation models and decision support systems Works with Digital teams to productionise models and deliver application front ends Translates results … high-quality inputs for models Designs, builds and trains data science products such as business models, predictive analytics tools, recommender systems, natural language processing, anomaly detection, forecasts, optimisation models and decision support systems Works with Digital teams to productionise models and deliver application front ends Translates results ...

contracts, capabilities, consumption patterns and priorities for internal and external use cases. Identify opportunities to leverage AI and machine learning to improve data classification, anomaly detection, validation, conflict resolution and other data‐intensive workflows. Work with Data Operations to move towards an exception‐based operating model, where … real‐time or near‐real‐time data processing. Experience applying AI/ML to geospatial or data‐quality problems, such as feature extraction, classification, anomaly detection or automated validation. Experience building developer‐facing products, APIs, SDKs or data services. Experience taking a platform from early‐stage architecture ...

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 ...

Proof‐of‐Concept to production‐grade, fleet‐level deployments. Preferred Experience working on GPU fleet management, hyperscale infrastructure, or AI training clusters. Experience building anomaly detection or failure prediction systems for hardware or distributed systems. Experience implementing distributed straggler detection or collective‐level performance analysis … curious about distributed systems failure modes, GPU performance pathologies, and reliability engineering at scale. You’re excited by the idea of moving from anomaly detection to prediction to autonomous root cause reasoning. You enjoy designing platforms that protect uptime, revenue, and customer trust through proactive systems thinking. ...

unstructured commercial and operational shipping data such as customs filings, fixtures, and SPAs. These inputs drive predictive systems that support energy-demand forecasting, anomaly detection, and real-time recommendations for physical and derivative trading. What You'll Be Doing As a Principal Data Scientist, reporting toVortexa … depth ofexpertiserather than the credential. Fluent in Python and broad in your modelling toolkit: withstrongexperience across regression and classification, clustering, time-series analysis, anomaly detection, sequence-to-sequencearchitecturesand stochasticoptimisation. Comfortable withsolvingambiguous problems:able to start with an abstract question, interrogate it, decide what is worth solving, choose ...

merchant fraud, abuse, chargebacks, and anomalous behaviour. Lead the adoption of modern modelling techniques, including: Transformers and sequence models Representation learning & embeddings Autoencoders and anomaly detection Graph/network-based models Semi-supervised and weakly supervised learning Own the end-to-end model lifecycle: problem framing, feature … Technical Skills: Expert-level Python and modern ML tooling. Strong hands-on experience with: Transformers, LSTM/sequence models Representation learning & embeddings Autoencoders & anomaly detection Experience operationalising models on AWS SageMaker (or equivalent). Strong understanding of model evaluation, explainability, and monitoring in high-risk environments. What ...

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. ...

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. ...

fraud interventions, balancing customer experience against loss reduction. Size fraud typologies across our product lines to inform prioritization and investment decisions. Build and maintain anomaly detection systems to surface novel fraud vectors before they scale. Work closely with fraud operations, engineers, product managers, and data analysts … technical findings clearly to non-technical stakeholders and translate insights into action. What Success Looks Like in This Role: Production-grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale. Well-designed experiments that successfully balance customer experience against ...

time network telemetry and automation triggers. Define observability strategies covering metrics, logs, traces, and network telemetry pipelines. Architect AIOps capabilities including closed‐loop automation, anomaly detection, and predictive analytics for network operations. Integrate OSS observability with cloud‐native monitoring stacks (Prometheus, Grafana, OpenTelemetry, Elasticsearch). Lead design … automation design for network operations. Experience with observability tooling: OpenTelemetry, Prometheus, Grafana, Jaeger, Loki, ELK Stack. Knowledge of ML/AI model integration for anomaly detection, root‐cause analysis, and predictive network management. Strong grasp of TM Forum frameworks: eTOM, TAM, SID, and Open Digital Architecture ...

driven mesh generation algorithms and automated geometry creation tools for aerodynamic applications. Conduct comprehensive analysis of wind tunnel data, including drift detection, anomaly identification, and statistical analysis to ensure data quality and reliability. Build and maintain robust CI/CD pipelines for AI model deployment, ensuring high … Strong proficiency in Python with the PyTorch framework. Understanding of computational geometry principles and familiarity with mesh generation algorithms. Experience with statistical analysis and anomaly detection techniques for large scientific datasets. Strong software engineering practices including CI/CD pipeline development and code quality standards. Excellent communication ...

templates, guardrails, so engineers can provision, deploy and operate services without raising a ticket. Embed AI-driven automation into the platform: intelligent cost optimisation, anomaly detection, auto-remediation and developer productivity tooling that actually gets used. Own cloud infrastructure on AWS, architecture, cost efficiency, reliability and security … equivalent) and confident building automation and tooling, not just configuring managed services. You actively build AI-powered tooling into platform and infrastructure workflows, cost anomaly detection, intelligent alerting, automated runbooks, not just use AI in your editor. You've built or contributed meaningfully to an internal developer ...

driven mesh generation algorithms and automated geometry creation tools for aerodynamic applications. Conduct comprehensive analysis of wind tunnel data, including drift detection, anomaly identification, and statistical analysis to ensure data quality and reliability. Build and maintain robust CI/CD pipelines for AI model deployment, ensuring high … Strong proficiency in Python with the PyTorch framework. Understanding of computational geometry principles and familiarity with mesh generation algorithms. Experience with statistical analysis and anomaly detection techniques for large scientific datasets. Strong software engineering practices including CI/CD pipeline development and code quality standards. Excellent communication ...

building practical tools to identify and resolve issues before they reach customers. The Role You will: Design and develop data quality checks covering validation, anomaly detection, freshness and coverage. Own and improve production web-scraping infrastructure, including Playwright, proxies and anti-bot handling. Build and maintain data … ship solutions efficiently. About You Strong Python and SQL skills, with hands-on dbt and BigQuery experience. Proven experience designing data quality, validation and anomaly detection processes. Production experience with web scraping at scale, ideally using Playwright or an equivalent. Experience with big data sets ...

versus standing access, and risk-gated credential issuance (e.g. a short-lived token issued against a CrowdStrike-style risk score). Behavioural baselining/anomaly detection for workloads — defining "normal" for a recurring workflow and catching deviation at volume. SIEM integration and action attribution: distinguishing an agent … onboarding standard (e.g. mandatory MCP interfaces) and win adoption through better defaults and developer experience, not mandate alone. Design SIEM integration, behavioural baselining, and anomaly detection for agentic workflows, and centralise siloed audit logs to satisfy both security and regulatory requirements. Take bounded beachheads (for example, authenticate ...

ensure the platform proactively responds to emerging fraud vectors and regulatory requirements. Establish platform guardrails and adoption criteria. Ensure platform capabilities support continuous monitoring, anomaly detection, chargeback reduction, and loss prevention. Provide structured updates to senior stakeholders and governance forums. Monitor platform performance, risks, costs and scalability … ensure the platform proactively responds to emerging fraud vectors and regulatory requirements. Establish platform guardrails and adoption criteria. Ensure platform capabilities support continuous monitoring, anomaly detection, chargeback reduction, and loss prevention. Provide structured updates to senior stakeholders and governance forums. Monitor platform performance, risks, costs and scalability ...

resolution Encode triage logic into automation pipelines so future instances are classified and escalated without manual intervention Apply ML and AI techniques — crash clustering, anomaly detection, pattern recognition — to build smarter triage pipelines Build debug tooling, scripts, and CI/CD integrations that surface OS-level signals … Exposure to automation frameworks, CI/CD pipelines, or scalable test systems Experience applying ML or AI techniques to systems problems — crash clustering, log anomaly detection, failure classification, or intelligent alert prioritization Familiarity with LLMs or generative AI tooling in an engineering context — prompt engineering, RAG pipelines ...

translating findings into practical actions. Using your expertise, you'll design and deploy AI-driven security capabilities such as threat detection, anomaly detection and incident response. You'll also advise on risk, compliance and regulation, ensuring we continue to meet industry standards as AI technologies ...