19 of 19 Permanent Anomaly Detection Jobs in London

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 ...

reuse. Schedule, monitor, and manage data pipelines using Airflow or similar workflow orchestration tools to ensure reliable, timely data delivery. Implement validation, reconciliation, and anomaly-detection controls to maintain data completeness, accuracy, and consistency. Apply AI to automate schema inference across structured and semi-structured data sources ...

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 ...

orchestration, retrieval-augmented generation (RAG), prompt engineering, and evaluation. Strong experience in the physical space: labs, manufacturing control, edge deployment of models, predictive and anomaly detection modeling, closed-loop control. Strong experience in lab automation and self-driving lab workflows: robotics, instrument integration, and digital-to-physical ...

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

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 ...

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 ...

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 ...

identify trends, patterns, and anomalies associated with potential ATO and Send Scam threats. Design and implement experiments to evaluate the effectiveness of fraud detection systems and continuously improve their performance. Collaborate with security analysts and engineers to translate business and security requirements into actionable data insights and solutions. … programming languages such as Python, R, or similar. Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL).Familiarity with anomaly detection, supervised, unsupervised learning methods, deep learning, and graph based solutionsDemonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex ...

DoingDesign and deliver the data products that make Azure cost visible and attributable across ASOS, including cost and usage pipelines, allocation and showback models, anomaly detection and reporting surfaces. Own the cost and usage data platform on Databricks, ingesting Azure Cost Management exports, reservation and Savings Plan ...

APIs. AI Innovation: Identify and implement high-impact opportunities for embedding GenAI and Agentic Workflows into IT Operations for alert analysis, remediation, and data anomaly detection. Governance & Health: Oversee CMDB health maintenance, data normalization, and reconciliation processes to ensure a "self-healing" IT environment. Collaborate: Act as a bridge ...

environment. Experience working in a software engineering or research team. Preferred qualifications: Experience with cybersecurity detection and response, building classifiers and anomaly detection systems at scale, taking safety defenses or mitigations from research concepts to scalable production systems. Experience collaborating on or leading applied ...

environment. Experience working in a software engineering or research team. Preferred qualifications: Experience with cybersecurity detection and response, building classifiers and anomaly detection systems at scale, taking safety defenses or mitigations from research concepts to scalable production systems. Experience collaborating on or leading applied ...

environment. Experience working in a software engineering or research team. Preferred qualifications: Experience with cybersecurity detection and response, building classifiers and anomaly detection systems at scale, taking safety defenses or mitigations from research concepts to scalable production systems. Experience collaborating on or leading applied ...

logistic regression and gradient boosting models. Ability to work autonomously, solve problems proactively, and thrive in a fast-moving environment. Exposure to clustering, anomaly detection, LLM applications, or agentic AI approaches would be advantageous. Strong commercial understanding of risk-based products, financial services, or payments environments ...

canary releases, blue/green deployments, feature flags or chaos/game days. Experience developing AI-assisted operations capabilities, such as alert enrichment, anomaly detection, triage support or runbook automation. Key SRE CompetenciesReliability engineering: SLOs, SLIs, error budgets, incident reduction and service health. Production excellence: monitoring, alerting ...

points, digital adoption challenges, and operational inefficiencies. Provide clear, actionable recommendations. Advance AI-native analytics Use Gen AI tools for automated insight generation, summarisation, anomaly detection, and workflow optimisation. Support experimentation & continuous improvement Analyse A/B tests and digital experience performance, quantifying customer and business impact. ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights. ...