76 to 100 of 148 Anomaly Detection Jobs in England

languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation.* Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation).* Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks.* Professional certifications such as EnCE, GASF ...

large remit, and we expect AI-assisted development to be embedded in how we work Apply AI tools to accelerate pipeline development, automated testing, anomaly detection and data quality monitoring Stay current with AI developments in the data engineering space and bring new approaches into the team ...

Code (IaC) is the organisational default and challenge inefficient legacy processes. FinOps & Governance: Enforce strict automated security and cost controls, real‐time cost‐anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches. Internal Platform ...

Code (IaC) is the organisational default and challenge inefficient legacy processes. FinOps & Governance: Enforce strict automated security and cost controls, real‐time cost‐anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches. Internal Platform ...

Code (IaC) is the organisational default and challenge inefficient legacy processes. FinOps & Governance: Enforce strict automated security and cost controls, real‐time cost‐anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches. Internal Platform ...

large remit, and we expect AI-assisted development to be embedded in how we workApply AI tools to accelerate pipeline development, automated testing, anomaly detection and data quality monitoringStay current with AI developments in the data engineering space and bring new approaches into the team's practiceIngenuity ...

deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) to customer production environments. Communicate results and trade-offs to senior stakeholders; steer roadmaps and influence product direction with evidence. Lead scoping ...

agent implementation. Design and implement AI-powered features within Compensation Collection, Shadow Payroll, and Equity products including intelligent data extraction from compensation statements, anomaly detection on payroll inputs, LLM-assisted user workflows, and retrieval-augmented generation (RAG) over tax and payroll guidance. Evaluate, integrate, and operationalize ...

build scalable, secure AI systems.What You'll Be DoingDesign, develop, and deploy machine learning models for traditional ML use cases, including forecasting, classification, and anomaly detection.Build and deliver Generative AI and LLM-powered applications using modern AI frameworks.Lead experimentation cycles, defining hypotheses, running evaluations, and iterating on models before ...

practical experience, or publications at venues (e.g., NeurIPS, ICLR, ICML, or EMNLP). 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 in adversarial machine learning, automated ...

detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall … maintaining a seamless user experience.Key job responsibilities- Own the end-to-end product strategy and roadmap for Traffic Quality solutions, including invalid traffic detection, prevention, and measurement systems.- Drive technical innovation in fraud detection methodologies, leveraging machine learning, ad forensics and device attestation.- Lead cross-functional ...

contribute to a forward-thinking, collaborative environment.The Data Scientist will be responsible for building and deploying machine learning models to support personalisation, recommendations, anomaly detection, and data insights. The role involves working within modern ML Ops practices and leveraging AI-powered development tools to increase efficiency … scale.Key ResponsibilitiesDevelop and deploy machine learning models for various use cases including personalisation and anomaly detectionImplement ML Ops practices including monitoring, continuous integration, and automated retrainingUse AI-assisted development tools such as Cursor and Copilot to enhance productivityCollaborate with engineers, DevOps, and leadership to ensure robust data pipelines ...

that strengthen our data foundations - ensuring our data is accurate, observable, and compliant. Your mission will be to reduce the mean time to detection and resolution of data incidents, by establishing data contracts between producers and consumers, developing robust data observability systems, and embedding governance and GDPR compliance … bridge technical depth with operational impact. Bonus Points Experience implementing automated compliance monitoring or policy-as-code systems. Familiarity with real-time anomaly detection for data pipelines. Experience contributing to or leading cross-functional data reliability initiatives. Prior experience in consumer or marketplace platforms. Passion for data ...

Observability AIOps Define integration frameworks with monitoring and observability platforms Ensure CMDB governance, data accuracy, and service mapping optimization Implement AIOps-driven event correlation, anomaly detection, and operational automation Establish governance standards, architectural best practices, and platform scalability measures Collaborate with business stakeholders, IT leadership, and operations ...

3+ years of experience in global data operations or support teams within peer firms, with a proven track record of delivering value.Apply expertise in anomaly detection methods, data quality workflows, and statistical best practices.Communicate effectively across technical and investment teams.Navigate complex data environments and support the necessary ...

classes, and delivers clarity when our clients need it most. As an ML Research Engineer, you will be working on exciting initiatives such as anomaly detection in bond time series data, dividend forecasting, gas emission estimation, and financial impact of controversies. Join us as a Senior ...

/Service/Marketing Cloud, integrations, or Apex best practices). Experience applying AI/ML in engineering workflows (e.g., coding assistants, test generation, anomaly detection, intelligent routing) or product features. Background in leading distributed teams and large‐scale refactoring or platform modernisation initiatives. Key Behaviours & Attributes ...

ensuring that the engineering team’s velocity is sustained by high-confidence automated processes. Lead the development of AI-augmented test strategies. Architect predictive anomaly detection systems and AI-driven test generation engines that evolve alongside our software, turning the test suite into an intelligent system that ...

ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc.Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc.Deep understanding of the GenAI landscape and agentic frameworks.Experience working in the full model lifecycle (including experimentation, training, testing, monitoring ...

automation languages (e.g. PowerShell, Python, SQL) for forensic workflow optimisation.Exposure to AI and machine learning applications in forensic and eDiscovery contexts (e.g. triage, clustering, anomaly detection, generative summarisation).Experience integrating forensic outputs within wider eDiscovery, incident response or regulatory frameworks.Professional certifications such as EnCE, GASF, GCFA, CISSP ...

improve data quality and surface commercial insights.Experience using AI tools to improve productivity, automate workflows, generate insights and enhance reporting.An interest in predictive analytics, anomaly detection and AI-driven monitoring, with a curiosity to explore new technologies that improve decision-making.Confidence working with agencies and multiple stakeholders ...

networks, underpinned by SON and closed-loop automation. Apply Generative AI & Autonomous Networks, identify and pilot GenAI use cases (AI-assisted planning, anomaly detection, predictive maintenance) and architect solutions aligned with TM Forum L0–L5 and ETSI ZSM frameworks. Productionise AI/ML models, collaborate with data ...

networks, underpinned by SON and closed-loop automation. Apply Generative AI & Autonomous Networks, identify and pilot GenAI use cases (AI-assisted planning, anomaly detection, predictive maintenance) and architect solutions aligned with TM Forum L0–L5 and ETSI ZSM frameworks. Productionise AI/ML models, collaborate with data ...

networks, underpinned by SON and closed-loop automation. Apply Generative AI & Autonomous Networks, identify and pilot GenAI use cases (AI-assisted planning, anomaly detection, predictive maintenance) and architect solutions aligned with TM Forum L0–L5 and ETSI ZSM frameworks. Productionise AI/ML models, collaborate with data ...

networks, underpinned by SON and closed-loop automation.Apply Generative AI & Autonomous Networks, identify and pilot GenAI use cases (AI-assisted planning, anomaly detection, predictive maintenance) and architect solutions aligned with TM Forum L0–L5 and ETSI ZSM frameworks.Productionise AI/ML models, collaborate with data science ...