1 to 25 of 40 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 ...

technologies. You will play a central role in designing, implementing, and continuously improving security capabilities that are increasingly enhanced by AI-driven detection, automation, and intelligent decision support.The position combines deep technical security engineering with forward-looking exploration of AI-enabled security systems, detection engineering … machine learning concepts for detection, or data-driven security analytics. Understanding of how AI can be applied to threat detection, anomaly detection, investigation support, and security operations automation. Awareness of emerging AI-driven attack techniques, including adversarial AI and automated exploitation methods. Familiarity ...

engineering role, responsible for defining the AI/ML roadmap for Enterprise Solutions while also building high-rigor analytical and predictive models for anomaly detection, variance analysis, drift detection, market and behavioral signals, forecasting, and prediction. The expectation is production-grade models, comparable in rigor … Experience combining statistical models, ML, semantic models, and rules-based logic where needed to achieve accuracy, stability, and explainability. Strong focus on data quality, anomaly detection, and monitoring, including metrics that surface real issues and drive sustained improvement. Experience & Mindset 20+ years working with analytics, data science ...

data monitoring (e.g., using Spark, Airflow, or similar distributed systems). Leverage and build agentic AI and LLM-powered systems to automate data exploration, anomaly detection, vendor evaluation, and investigative workflows, increasing the speed and depth of insight generation. Build and optimize models using a variety … support of fraud detection and identity verification use cases. Own data quality and integrity for critical datasets, implementing monitoring, validation checks, and anomaly detection to ensure reliable input to models and downstream decision systems. Take ownership of project outcomes from scoping through delivery, managing data ...

alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support the use of analytics-led monitoring for anomaly detection and predictive fault identification. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational guides. Support knowledge …/IP, BGP, OSPF, VLANs and optical networks. Familiarity with Grafana, Prometheus or similar observability tools. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Knowledge of SNMP, NetFlow/IPFIX or syslog pipelines would be useful. Scripting or automation ...

alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support the use of analytics-led monitoring for anomaly detection and predictive fault identification. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational guides. Support knowledge …/IP, BGP, OSPF, VLANs and optical networks. Familiarity with Grafana, Prometheus or similar observability tools. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Knowledge of SNMP, NetFlow/IPFIX or syslog pipelines would be useful. Scripting or automation ...

alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support the use of analytics-led monitoring for anomaly detection and predictive fault identification. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational guides. Support knowledge …/IP, BGP, OSPF, VLANs and optical networks. Familiarity with Grafana, Prometheus or similar observability tools. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Knowledge of SNMP, NetFlow/IPFIX or syslog pipelines would be useful. Scripting or automation ...

thresholds and SLA-led alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support analytics-led monitoring for anomaly detection and predictive fault identification where relevant. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational … VLANs and optical or fibre environments. Familiarity with dashboarding, alert tuning, service health monitoring and operational reporting. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Scripting or automation experience, such as Python or Bash, would be advantageous. Comfortable working ...

thresholds and SLA-led alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support analytics-led monitoring for anomaly detection and predictive fault identification where relevant. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational … VLANs and optical or fibre environments. Familiarity with dashboarding, alert tuning, service health monitoring and operational reporting. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Scripting or automation experience, such as Python or Bash, would be advantageous. Comfortable working ...

thresholds and SLA-led alerting. Work closely with network and operational teams to align monitoring with changing infrastructure requirements. Support analytics-led monitoring for anomaly detection and predictive fault identification where relevant. Improve monitoring architecture, tooling, documentation and handover processes. Produce clear runbooks, escalation paths and operational … VLANs and optical or fibre environments. Familiarity with dashboarding, alert tuning, service health monitoring and operational reporting. Exposure to AI/ML-led monitoring, anomaly detection or predictive fault identification would be beneficial. Scripting or automation experience, such as Python or Bash, would be advantageous. Comfortable working ...

lookups, event types, tags, and field extractions. · Integrate ITSI and Splunk Cloud with CMDB/ITSM systems, webhook automation, and AIOps/ML-based anomaly detection frameworks. · Troubleshoot slow or high-latency searches, identify bottlenecks, and implement best-practice SPL optimization. · Develop, optimize, and maintain advanced … proficiency in SPL, search optimization, and dashboard development. · Deep experience with ITSI, including service modelling, KPIs, thresholds, NEAP, and Service Analyzer. · Experience with MLTK, anomaly detection, forecasting, and operationalizing ML models. · Strong understanding of observability concepts (logs, metrics, traces, golden signals). · Hands-on experience with data ...

Scale Up Consultancy, is building the execution layer of an agentic decisioning powered by specialised predictive agents: → Demand forecasting → Churn modelling → Propensity scoring → Anomaly detection What makes this different Your models won’t sit in isolation. They’ll live inside agentic workflows where they must be: Explainable … engineering at scale Embedding ML into agent-based systems Core stack Python · scikit-learn · MLflow · SQL · Docker · Feature Stores Nice to have Explainable AI · Anomaly Detection · LLM/NLP integration · Real-time inference ...

other analysis and automation techniques to complex problem domains within the Modaxo group of companies, including: Computer Vision (object detection, image segmentation, anomaly detection, text extraction). Scheduling & Planning (resource allocation, constraint optimization, fleet routing). Deep Learning & LLMs (transformers, reinforcement learning, generative ...

neutralizing sophisticated fraud. As a Principal Data Scientist, you'll play a critical role in architecting, developing, and deploying cutting‐edge fraud detection and prevention systems within our SaaS solutions. You will have a direct impact on SheerID’s growth by safeguarding the integrity of our platform. … charge in staying ahead of evolving fraud tactics. We're seeking a passionate and experienced data science leader with a deep foundation in anomaly detection, pattern recognition, and machine learning. You thrive in collaborative environments, possess strong leadership qualities, and are committed to crafting high‐quality, secure ...

engineering practices across the team. Key Responsibilities Lead the design, development, evaluation, and deployment of machine learning models for predictive, classification, recommendation, anomaly detection, forecasting, and optimization use cases. Translate business and product requirements into well-defined analytical approaches, model strategies, feature sets, evaluation methods, and deployment … downstream business systems. Design and implement MLOps practices including experiment tracking, model versioning, automated deployment, CI/CD for ML, monitoring, drift detection, retraining strategies, and rollback readiness. Establish model performance baselines and monitor production behaviour for accuracy, drift, latency, stability, explainability, and business outcomes. Contribute to best ...

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 ...

design, development, and evaluation of machine learning, statistical, and graph-based algorithms for entity-resolution, identity trust scoring, and anomaly detection on massive datasets. Architect and optimize graph-based identity representations (identity graph structure, linkage rules, clustering) to improve match rates, reduce false positives/negatives … graph databases and/or graph frameworks (Neo4j, AWS Neptune, GraphFrames, DGL, PyTorch Geometric) and graph algorithms for clustering, link prediction, and community detection is strongly preferred. Solid SQL skills and experience working with large-scale analytical data stores. Experience in at least one of: identity verification, fraud ...

infrastructure everything else depends on. Intelligence is the layer above the data - AI-powered insights, predictive models built on Databricks and Snowflake, anomaly detection, and agentic features. This is a full-stack role. You'll own features from the data layer to the customer-facing interface. ...

into Unity Catalog, ensuring proper governance, lineage, and discoverability. Platform Collaboration & Delivery * Support the ML/Data Scientist in preparing clean, structured datasets for anomaly detection and asset performance modelling. * Contribute to technical documentation and ensure pipelines are maintainable and transferable. * Stay current on Databricks and Azure ...

clear judgment on when AI is appropriate versus deterministic or rules-based approaches. Strong understanding of analytics and AI in production (e.g. data quality, anomaly detection, fraud/AML, workflow automation) and understands what it takes to run these reliably in regulated environments. Designs with security ...

Engines, Revenue Management tools). Data Quality & Integrity: Ensure consistent, accurate, and timely data flow across systems. Develop processes for data validation, reconciliation, and anomaly detection. Cross-Functional Collaboration: Work closely with operations, marketing, finance, and executive teams to understand data needs and translate them into analytical solutions that ...

research and develop deep learning models to solve real-world problems and apply them to tasks such as identifying bad actors, preventing fraud, building anomaly detection models, and analytics at a high scale. As a senior manager, you are expected to create an alignment across different divisions … collaborate and perform shared goals. Successful outcomes in this role will significantly impact the business. Responsibilities: Lead the development and optimization of fraud detection systems using machine learning and rule-based engines. Work closely with management, product, engineering, compliance, legal, and security teams to align, present, and implement ...

diverse global markets, ensuring metrics account for regional regulatory and language differences. Advanced Analytics & AI: Leverage Python and Gen AI tools to automate anomaly detection, summarization, and recurring insight generation. Root Cause Discovery: Conduct deep-dives into the end-to-end customer journey to uncover friction points ...

diverse global markets, ensuring metrics account for regional regulatory and language differences. Advanced Analytics & AI: Leverage Python and Gen AI tools to automate anomaly detection, summarization, and recurring insight generation. Root Cause Discovery: Conduct deep-dives into the end-to-end customer journey to uncover friction points ...

diverse global markets, ensuring metrics account for regional regulatory and language differences. Advanced Analytics & AI: Leverage Python and Gen AI tools to automate anomaly detection, summarization, and recurring insight generation. Root Cause Discovery: Conduct deep-dives into the end-to-end customer journey to uncover friction points ...