1 to 25 of 125 Permanent Anomaly Detection Jobs in London

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 ...

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 ...

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 ...

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 ...

that detect when an outcome deviates from its expected value in a statistically significant way, using seasonality-aware baselines, forecast residuals, control limits, and anomaly detection rather than static thresholds. Route those exceptions to accountable owners with context, likely drivers, and a recommended next action; actively tune … Domo, and Tableau specifically. Proficiency in Python or R for prototyping, and familiarity with common statistical and ML libraries and MLOps concepts. Experience deploying anomaly detection at scale, including alert routing, suppression, and fatigue management. Familiarity with data product and data mesh operating models, domain-aligned ownership ...

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 ...

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. ...

experience applying AI, machine learning, advanced analytics or data science techniques to generate insights and support business decision-making. This may include forecasting, optimisation, anomaly detection, predictive modelling, simulation, recommendation engines, digital twins, scenario analysis, or decision-intelligence solutions that improve operational performance and business outcomes.AI-driven … comparable tools to analyse system performance, application behaviour and operational processes. Familiarity with distributed tracing, telemetry data, root-cause analysis, service dependency mapping, anomaly detection and AI-assisted operational insights would be advantageous.Entity resolution and contextual intelligence: experience with Quantexa or comparable decision intelligence, entity resolution ...

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 ...

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 to Vortexa … rather than the credential. Fluent in Python and broad in your modelling toolkit: with strong experience across regression and classification, clustering, time-series analysis, anomaly detection, sequence-to-sequence architectures and stochastic optimisation. Comfortable with solving ambiguous problems: able to start with an abstract question, interrogate ...

/ML initiatives - from problem framing and modeling to evaluation, deployment, and iteration - directly improving core product workflows (invoice understanding, approval matching, reconciliation, anomaly detection, and user-assist).Your responsibilitiesOwn LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations. Define evaluation & monitoring ...

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 ...

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 ...

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 ...

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 ...

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 ...

scalability, and ease of maintenance. AI/ML Model Development Develop, train, and evaluate machine learning models that address core FinOps use cases: cost anomaly detection, spend forecasting, workload rightsizing recommendations, and commitment coverage optimization. Implement and maintain MLOps pipelines for model versioning, automated retraining, performance monitoring … drift detection as cloud usage patterns evolve. Experiment with and apply generative AI and LLM capabilities to FinOps workflows - such as natural language interfaces for cost querying, AI-assisted tagging remediation, or intelligent cost allocation suggestions. Collaborate with FinOps analysts to validate model outputs against business expectations, refining ...

than AI tooling alone. What you’ll be doing: Machine Learning & Advanced Analytics Develop machine learning models for forecasting, classification, recommendation, optimisation, clustering and anomaly detection. Apply statistical and machine learning techniques to analyse structured and semi-structured datasets. Perform exploratory data analysis, feature engineering, model training, validation ...

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 ...

into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.* SQL and large-scale data analysis.* Cloud-based data science platforms ...

licence optimisation, hardware rightsizing, capacity rebalancing, decommissioning, and vendor renegotiation Cost Governance Gaps — Assess and strengthen cost governance processes including approval workflows, budget controls, anomaly detection, and policy enforcement Data Normalisation — Normalise cost data from disparate sources into a unified cost model, enabling consistent reporting across business … months) based on value and feasibility Reporting & Dashboards — Design and recommend live/near-real-time cost dashboards with drill-down capabilities, trend analysis, anomaly alerts, and executive reporting views FINOPS PERSONA COLLABORATION Executives (CTO, CFO, CIO) — Present cost visibility dashboards, business cases for optimisation, and FinOps maturity roadmaps ...

licence optimisation, hardware rightsizing, capacity rebalancing, decommissioning, and vendor renegotiation Cost Governance Gaps — Assess and strengthen cost governance processes including approval workflows, budget controls, anomaly detection, and policy enforcement Data Normalisation — Normalise cost data from disparate sources into a unified cost model, enabling consistent reporting across business … months) based on value and feasibility Reporting & Dashboards — Design and recommend live/near-real-time cost dashboards with drill-down capabilities, trend analysis, anomaly alerts, and executive reporting views FINOPS PERSONA COLLABORATION As defined by FinOps.org, this role works with all key FinOps personas: Executives ...