1 to 25 of 32 Anomaly Detection Jobs in England

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 ...

product stakeholders, and where ownership and innovation are encouraged. The Role You will • Co‐own an internal Python framework used to build KPI and anomaly detection trackers. • Take ownership of an anomaly detection system built on AWS, ensuring it is robust, scalable and production … work with the core data science stack such as pandas. • Experience contributing to shared codebases and managing releases. • Knowledge of SQL. • Bonus skills include anomaly detection experience, Slack API integrations, and strong SQL capabilities. What They Offer • Opportunity to co‐own critical internal frameworks and production systems. ...

automated alerting. Enhance end-to-end pipeline resilience, monitoring, observability, failure handling, and recovery mechanisms. Integrate AI/ML features to boost reliability, anomaly detection, and operational efficiency. Collaborate closely with Data Product teams, Analytics Engineering, and Data Science to deliver production-grade data solutions. Ensure pipelines … domain platforms. Experience in enterprise data transformation programmes with stringent SLAs and reliability expectations. Preferred Experience: Exposure to AI-enabled pipeline capabilities, such as anomaly detection or intelligent monitoring. Good understanding of MLOps or supporting deployment of ML models into production environments. Experience with CI/ ...

clearance and a strong background in building and deploying ML solutions within cloud environments. Key Responsibilities: Develop and deploy machine learning models for anomaly detection Build proofs of concept (PoCs) to validate data science approaches Design and implement automated workflows and pipelines Work with large-scale datasets … mandatory) Strong proficiency in Python Hands-on experience with AWS , particularly SageMaker Experience with Streamlit for rapid prototyping and PoC development Solid understanding of anomaly detection techniques Experience building data workflows/pipelines Desirable: Experience working in secure/government environments Knowledge of MLOps best practices Familiarity ...

semantic layers, Foundry-style systems) Ensure semantic compliance, data integrity and reasoning-readiness Data Quality, Observability & Lineage Implement robust data quality frameworks (validation, profiling, anomaly detection) Build observability into pipelines (lineage tracking, logging, freshness monitoring, schema drift detection) Ensure alignment with governance, security and industry ...

support consistent and governed development. Enable Gen AI and Co pilot Studio adoption by producing AI ready datasets and identifying opportunities for automation, anomaly detection, and forecasting. Optimise BI workflows by leveraging AI for documentation, requirements capture, DAX optimisation, and natural language querying. Key Responsibilities Design ...

cost. Leverage AIOps and observability tools (e.g. Dynatrace, Datadog, New Relic, Elastic) to proactively monitor service health and performance. Utilise predictive alerting and anomaly detection to prevent incidents and optimise delivery priorities. Coordinate across internal teams, vendors, and stakeholders to ensure seamless delivery. Client Communication ...

Scientist (Machine Learning) will apply statistical and machine learning techniques to real commercial datasets, producing outputs such as impact analysis, ROI modelling, forecasting, and anomaly detection. The emphasis is on practical model delivery, documentation, and handover, rather than long-term operational ownership. As our new Data Scientist (Machine Learning … will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering team Document and hand over deliverables If you are an experienced ...

Scientist (Machine Learning) will apply statistical and machine learning techniques to real commercial datasets, producing outputs such as impact analysis, ROI modelling, forecasting, and anomaly detection. The emphasis is on practical model delivery, documentation, and handover, rather than long-term operational ownership. As our new Data Scientist (Machine Learning … will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering team Document and hand over deliverables If you are an experienced ...

classification, data extraction, validation workflows). Design, implement, and integrate AI services and pipelines, such as Machine learning/rules-based components for classification, anomaly detection, and routing (e.g. flagging potentially incorrect invoices or exceptional cases). Fine-tuned language models or specialized inference models deployed ...

clients to scope, design, and deliver operationally-ready AI and ML solutions Key Responsibilities: Design, develop, and deploy machine learning models for forecasting, classification, anomaly detection, and LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly Transition validated experiments into production-ready ...

exciting opportunity for an RF-focused Data Scientist/Research Engineer to join a stealth-mode start-up developing novel UAV/detection systems. This role offers the chance to work at the cutting edge of RF hardware, software-defined radio, and intelligent signal processing helping shape … wireless protocols and physical-layer signal structures (e.g. Wi-Fi, LTE, LoRa) Ability to design machine learning or statistical models for signal classification, anomaly detection or emitter identification MUST be eligible for SC Clearance due to the nature of the work Responsibilities for RF Data Scientist/ ...

implement custom machine learning models for signal processing, sensor fusion, and system optimisation Design models for applications such as noise suppression, drift compensation, anomaly detection, and adaptive calibration Build and maintain robust data pipelines to process high-dimensional experimental and time-series datasets Train, validate, and optimise ...

hands-on R&D role involves analysing complex RF datasets, developing advanced signal-processing pipelines, and contributing to cutting-edge UAV/drone detection technologies. You will play a key role in prototyping new sensing capabilities, working with SDRs, designing real-world RF experiments, and integrating machine-learning … front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration ...

classification, data extraction, validation workflows). Design, implement, and integrate AI services and pipelines, such as Machine learning/rules-based components for classification, anomaly detection, and routing (e.g. flagging potentially incorrect invoices or exceptional cases). Fine-tuned language models or specialized inference models deployed ...

Modeling Consultant to design and implement comprehensive threat models for 90-100 diverse applications. The consultant will evaluate application-generated logs, develop threat detection strategies, and report findings … Information Security team. This role requires deep expertise in Microsoft Azure security tools, log analytics, and automation to enhance the customer’s application anomaly detection capabilities. Key Responsibilities: Develop detailed threat models tailored for a large portfolio of applications with varying threat categories. Analyze logs generated ...

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 Transition validated experiments into production-ready solutions, working ...

Embed Zero Trust and least privilege principles across enterprise systems and privileged roles. Develop and automate identity governance processes, leveraging AI/ML for anomaly detection and remediation. Oversee Conditional Access, risk-based authentication, and device/state-based access controls. Integrate IAM with ...

Threat Modelling Consultant to design and implement comprehensive threat models for 90-100 diverse applications. You will evaluate application-generated logs, develop threat detection strategies and report findings … Information Security team. This role requires deep expertise in Microsoft Azure security tools, log analytics and automation to enhance the customer's application anomaly detection capabilities. Key Responsibilities: Develop detailed threat models tailored for a large portfolio of applications with varying threat categories Analyse logs generated ...

Arbor, Radwhere, Riverbed, A10, ExtraHop Familiarity with security audits, RFP/RFI responses Exposure to security analytics tools and techniques, such as log analysis, anomaly detection, or traffic monitoring, with an interest in developing stronger skills. Understanding of full packet capture and analysis concepts, or hands ...

enforce tagging strategies, resource governance and cost allocation frameworks Implement and manage Azure Policy controls to ensure compliance and cost discipline at scale Lead anomaly detection processes, enabling rapid identification and response to unexpected spend Optimisation & Strategy Drive a continuous optimisation programme covering right-sizing, reserved instances ...

Have: IBM Integration ecosystem exposure (TechXchange, User Groups). Migration experience (legacy/MuleSoft webMethods). AI in integration (GenAI co-pilots, agent frameworks, anomaly detection). Dashboarding/observability for APIs/B2B/IS. Ways of Working: Hybrid/remote, with on-site workshops across ...

Have: IBM Integration ecosystem exposure (TechXchange, User Groups). Migration experience (Legacy/MuleSoft webMethods). AI in integration (GenAI co-pilots, agent frameworks, anomaly detection). Dashboarding/observability for APIs/B2B/IS. Ways of Working: Hybrid/remote, with on-site workshops across ...

Have: IBM Integration ecosystem exposure (TechXchange, User Groups). Migration experience (legacy/MuleSoft webMethods). AI in integration (GenAI co-pilots, agent frameworks, anomaly detection). Dashboarding/observability for APIs/B2B/IS. Ways of Working: Hybrid/remote, with on-site workshops across ...

establish observability standards. To thrive in this role, you should have extensive experience in designing and configuring the following within Dynatrace: Application performance monitoring Anomaly detection profiles Alerting rules and alert profiles Synthetic monitoring Log monitoring Real User Monitoring (RUM) to capture and analyze end-user experiences ...