1 to 25 of 27 Anomaly Detection Jobs in the UK

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

using MLOps frameworks. Establish and enforce data governance policies, stewardship models, and metadata management practices Monitor and improve data quality using rule-based profiling, anomaly detection, and GenAI-powered automation Support GenAI initiatives through data readiness, synthetic data generation, and prompt engineering. Mandatory Skills Cloud Platforms: Deep … Experience in defining semantic layers, asset hierarchies, and contextual models. Data Governance: Hands-on experience Data Quality: Ability to implement profiling, cleansing, standardization, and anomaly detection frameworks. Security & Compliance: Knowledge of data privacy, access control, and secure data exchange protocols. Defining and creating MLOPs pipeline Good ...

IR35 Project Overview You’ll join a fast-scaling fintech organisation undergoing a major AI-led transformation focused on building next-generation fraud detection, credit risk, real-time decisioning, and forecasting platforms. The programme is replacing legacy, rule-based systems with machine learning-driven intelligence to improve transaction … Engineering, AI Engineering or Applied Data Science (fintech, banking, payments, or financial services strongly preferred). Design, build and productionise fraud detection, anomaly detection, transaction monitoring, credit risk and forecasting models. Develop time-series forecasting models for demand, liquidity, transaction volume and customer behaviour prediction. ...

building intelligent agents that detect anomalies and glitches in gameplay, ensuring an exceptional player experience. Key Responsibilities Design and implement ML models for anomaly detection in video streams and gameplay data. Apply computer vision and video analysis techniques to identify irregularities and bugs. Explore advanced methods such … background in machine learning research; PhD preferred (or equivalent experience in game development). Expertise in Python, PyTorch, and TensorFlow. Experience with video-based anomaly detection, computer vision, and streaming analysis. Gaming industry experience is a plus. Ability to lead projects and guide technical direction ...

communicate findings in clear, non-technical terms. Modelling, experimentation, and impact Build and deploy predictive and prescriptive models (predictive maintenance, yield/defect forecasting, anomaly detection, capacity planning, SPC-aware models). Deployment, governance, and scale Operationalise models in the cloud with robust MLOps practices, including versioning … monitoring, drift detection, retraining, and documentation. Create model cards and explainability artifacts to support trust and adoption by operators and leadership. Develop scalable data pipelines and reusable analytics components; enable near real-time scoring and alerting for process deviations. Collaboration, enablement, and change management Partner with process engineers ...

data providers Big Tech or adjacent industries where work maps structurally to quant data problems (e.g. large-scale recommender systems, NLP on unstructured data, anomaly detection, knowledge graphs) Smaller teams with broad ownership and responsibility Compensation & Benefits Fully guaranteed, competitive compensation Education allowance for dependent children ...

Deep understanding of service assurance, fulfillment, and network operations; hands-on with digital twin frameworks (topology/graph modeling, intent-based orchestration), AIOps platforms (anomaly detection, noise reduction, predictive insights), and streaming/data pipelines (Kafka, Pub/Sub, Dataflow) Familiarity with cloud-native (GCP/Azure ...

chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards ...

analysis. Work with the Quality team to automate FAI checks, SPC monitoring, supplier performance analysis, and NCR triage. Assist Production with digital work instructions, anomaly detection, and AI-supported training materials. Enterprise-level AI integration: Contribute to long-term AI architecture decisions choosing tools, shaping governance ...

deploy production-grade ML and GenAI solutions in high-impact operational environments. What youll be doing: Design and build ML models across forecasting, classification, anomaly detection, and GenAI/LLM use cases Lead experimentation cycles: hypothesis, evaluation, iteration, and validation Take successful ML approaches into production, including ...

scalability, and reliability. Leverage tools like Alteryx for data transformation and workflow efficiency. Data Innovation & Automation: Apply AI tools and automation to enhance reporting, anomaly detection, and performance forecasting. Support the integration of predictive analytics and natural language query tools for improved data access and insight. Enablement ...

scalability, and reliability. Leverage tools like Alteryx for data transformation and workflow efficiency. Data Innovation & Automation: Apply AI tools and automation to enhance reporting, anomaly detection, and performance forecasting. Support the integration of predictive analytics and natural language query tools for improved data access and insight. Enablement ...

regulated sector objectives. This is a London-based role with hybrid working support. Key Responsibilities: Design, develop, and iterate ML models for forecasting, classification, anomaly detection, and GenAI/LLM applications. Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly. Transition validated experiments into ...

Teams integrations, and telemetry based improvements. Drive AI enabled operations using Bedrock/SageMaker and the Model Context Protocol (MCP) for log analysis, anomaly detection, and incident workflows. Define cloud guardrails and enforce security controls, including IAM boundaries, SCPs, OPA policies, tagging, centralized logging, and audit tooling. ...

direction across architecture, data infrastructure, analytics systems, and compute pipelines, while integrating emerging intelligence-driven capabilities such as automated risk scoring, alerting, reporting, and anomaly detection. You’ll work cross-functionally with Product, Analytics, and Customer Success, operating as a technical and strategic leader shaping the next phase … integrations. Data Infrastructure & Analytics Scale the data platform to support broader asset coverage, higher throughput, and more sophisticated analysis. Develop advanced analytics capabilities including anomaly detection, cross-chain signals, and automated scoring models. Ensure data accuracy, quality, and resiliency across pipelines and computation layers. Emerging AI & Automation ...

. Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . Graph based ML familiarity: link prediction, anomaly detection, traversal, community detection. NLP/NLU skills: entity/relation recognition, summarisation, topic modelling, classification, coreference resolution. Visualization and communication Graph ...

environment where you will apply cutting-edge machine learning methods to unique datasets. Key responsibilities: Lead and contribute to ML projects, including forecasting, classification, anomaly detection, and LLM/GenAI applications. Design experiments, formulate hypotheses, evaluate results, and iterate rapidly to validate approaches. Transition experimental models into ...

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 ...

dashboards and visualisations, communicating insights in accessible, non-technical language Modelling & Deployment Develop and deploy predictive and prescriptive models (e.g. predictive maintenance, defect forecasting, anomaly detection, capacity planning) Operationalise models using cloud and MLOps best practices, including monitoring, documentation, retraining, and explainability Collaboration & Change Work closely with ...

frameworks (e.g., NIST, ISO 27001, SOC2, supply-chain risk standards). Understanding of machine-learning/AI concepts (e.g., risk-scoring models, graph analytics, anomaly detection). Experience working with enterprise B2B customers, especially security teams, procurement/supply-chain teams. Experience with visualising large-scale graph ...

Monitoring Infrastructure : Build real-time systems that track agent behaviour across risk factors including agent-to-agent interactions, privilege escalation attempts, emergent capability detection, and behavioural drift from baseline parameters • Risk Assessment Engine : Design algorithms that quantify AI risk in financial terms (£X exposure), map behaviours to regulatory … Integration : Implement monitoring for agent communication protocols (Model Context Protocol, Agent2Agent, Agent Connect Protocol) as they mature, ensuring authenticated and logged inter-agent communications • Anomaly Detection : Develop ML systems that identify when agents exhibit unexpected strategies, attempt unauthorized actions, or drift from intended behaviour—catching issues before ...

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 ...

capabilities across multi-domain telecom networks. The role involves translating operator needs into clear product requirements, enabling automation use cases such as event correlation, anomaly detection, RCA, predictive analytics, and auto-remediation across RAN, Transport, Core, and Cloud environments. The ideal candidate has deep knowledge ...

will be responsible for gathering, analysing, and translating business and operational requirements into clear functional specifications. Your work will directly enhance real-time monitoring, anomaly detection, event correlation, RCA, and predictive insights across telecom networks . Key Responsibilities: Collaborate closely with NOC/SOC, network operations, service ...

areas include: Data analysis of the telemetry from Ground and Space Assets to ensure reliable and efficient performance Develop operational automation for mission execution, anomaly detection and resolution, space situational awareness, and performance monitoring. Develop a data platform that allow for flexible data storage and analytics Maintain ...