18 of 18 Remote/Hybrid Anomaly Detection Jobs in England

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

alerting workflows. Experience with streaming telemetry, including tools and protocols such as gNMI, gRPC, Telegraf or gNMIc. Exposure to AI or ML-driven monitoring, anomaly detection or predictive fault identification. Strong networking fundamentals across TCP/IP, BGP, OSPF, VLANs and optical networks. Comfortable working independently ...

alerting workflows. Experience with streaming telemetry, including tools and protocols such as gNMI, gRPC, Telegraf or gNMIc. Exposure to AI or ML-driven monitoring, anomaly detection or predictive fault identification. Strong networking fundamentals across TCP/IP, BGP, OSPF, VLANs and optical networks. Comfortable working independently ...

alerting workflows. Experience with streaming telemetry, including tools and protocols such as gNMI, gRPC, Telegraf or gNMIc. Exposure to AI or ML-driven monitoring, anomaly detection or predictive fault identification. Strong networking fundamentals across TCP/IP, BGP, OSPF, VLANs and optical networks. Comfortable working independently ...

whitepapers , contributing to product strategy 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 ...

Monitor and evaluate emerging IAM trends (e.g., passwordless authentication, decentralised identity, adaptive access controls). - Lead automation and governance initiatives, including machine-learning-based anomaly detection. - Integrate and optimise multi-factor authentication, biometrics, and mobile identity capabilities. - Drive adoption of identity threat detection and response (ITDR) solutions. ...