51 to 75 of 88 Anomaly Detection Jobs in England

GSQL, AQL, SPARQL etc. depending on stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link prediction, anomaly detection) Optimize graph performance, scaling, and query efficiency Liaise with client stakeholders: translate business problems into graph solutions Mentor junior engineers, contribute to propositions, and support POCs More ❯

teams in peer firm(s) with a demonstrable track record delivering the value described for this role Experience with methods, tools, statistics, and best practices for autonomous and discretionary anomaly detection, and data quality workflow Excellent written and verbal communication skills; experience working with technical, investment and senior leadership teams Experience as a leader in a team More ❯

mindset: Self-starter who moves fast, wears multiple hats, and ships iteratively Bonus Points Experience with text analytics, NLP, or customer experience (CX) analytics Background in time-series analysis, anomaly detection, or forecasting Prior work at analytics agencies or consulting delivering bespoke reporting Exposure to AI infrastructure (vector databases, embeddings, semantic search) Experience at early-stage startups More ❯

mindset: Self-starter who moves fast, wears multiple hats, and ships iteratively Bonus Points Experience with text analytics, NLP, or customer experience (CX) analytics Background in time-series analysis, anomaly detection, or forecasting Prior work at analytics agencies or consulting delivering bespoke reporting Exposure to AI infrastructure (vector databases, embeddings, semantic search) Experience at early-stage startups More ❯

mindset: Self-starter who moves fast, wears multiple hats, and ships iteratively Bonus Points Experience with text analytics, NLP, or customer experience (CX) analytics Background in time-series analysis, anomaly detection, or forecasting Prior work at analytics agencies or consulting delivering bespoke reporting Exposure to AI infrastructure (vector databases, embeddings, semantic search) Experience at early-stage startups More ❯

mindset: Self-starter who moves fast, wears multiple hats, and ships iteratively Bonus Points Experience with text analytics, NLP, or customer experience (CX) analytics Background in time-series analysis, anomaly detection, or forecasting Prior work at analytics agencies or consulting delivering bespoke reporting Exposure to AI infrastructure (vector databases, embeddings, semantic search) Experience at early-stage startups More ❯

mindset: Self-starter who moves fast, wears multiple hats, and ships iteratively Bonus Points Experience with text analytics, NLP, or customer experience (CX) analytics Background in time-series analysis, anomaly detection, or forecasting Prior work at analytics agencies or consulting delivering bespoke reporting Exposure to AI infrastructure (vector databases, embeddings, semantic search) Experience at early-stage startups More ❯

practices including DevOps, SRE, IaC, and cloud-native design (Azure, AWS, or GCP). Experience implementing AI/ML-enabled tooling within engineering practices (eg code copilots, test generation, anomaly detection, CI/CD acceleration). Demonstrable success in improving engineering velocity, quality, and scalability. Strong leadership and communication skills, with the ability to align technology, people More ❯

practices including DevOps, SRE, IaC, and cloud-native design (Azure, AWS, or GCP). Experience implementing AI/ML-enabled tooling within engineering practices (eg code copilots, test generation, anomaly detection, CI/CD acceleration). Demonstrable success in improving engineering velocity, quality, and scalability. Strong leadership and communication skills, with the ability to align technology, people More ❯

practices including DevOps, SRE, IaC, and cloud-native design (Azure, AWS, or GCP). Experience implementing AI/ML-enabled tooling within engineering practices (eg code copilots, test generation, anomaly detection, CI/CD acceleration). Demonstrable success in improving engineering velocity, quality, and scalability. Strong leadership and communication skills, with the ability to align technology, people More ❯

practices including DevOps, SRE, IaC, and cloud-native design (Azure, AWS, or GCP). Experience implementing AI/ML-enabled tooling within engineering practices (eg code copilots, test generation, anomaly detection, CI/CD acceleration). Demonstrable success in improving engineering velocity, quality, and scalability. Strong leadership and communication skills, with the ability to align technology, people More ❯

embedded dashboards, cross-source joins, and both human and AI-native querying (e.g. Text-to-SQL). Leverage in-app instrumentation (session replays, logs, engagement events) to enable observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions Lead the development of agentic capabilities—such as natural language querying, AI-generated dashboards, and real-time recommendations More ❯

embedded dashboards, cross-source joins, and both human and AI-native querying (e.g. Text-to-SQL). Leverage in-app instrumentation (session replays, logs, engagement events) to enable observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions Lead the development of agentic capabilities—such as natural language querying, AI-generated dashboards, and real-time recommendations More ❯

embedded dashboards, cross-source joins, and both human and AI-native querying (e.g. Text-to-SQL). Leverage in-app instrumentation (session replays, logs, engagement events) to enable observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions Lead the development of agentic capabilities—such as natural language querying, AI-generated dashboards, and real-time recommendations More ❯

embedded dashboards, cross-source joins, and both human and AI-native querying (e.g. Text-to-SQL). Leverage in-app instrumentation (session replays, logs, engagement events) to enable observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions Lead the development of agentic capabilities—such as natural language querying, AI-generated dashboards, and real-time recommendations More ❯

embedded dashboards, cross-source joins, and both human and AI-native querying (e.g. Text-to-SQL). Leverage in-app instrumentation (session replays, logs, engagement events) to enable observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions Lead the development of agentic capabilities—such as natural language querying, AI-generated dashboards, and real-time recommendations More ❯

build tech solutions Process, cleanse and analyse field data (e.g. sensor, geodata, drone imagery, underwater survey data) and produce actionable insights Prototype models and algorithmic solutions (e.g. predictive maintenance, anomaly detection, scheduling optimisation) Work with external partners, GIS/remote sensing, visualization and tooling frameworks Assist in digital transformation initiatives — documenting code, developing dashboards and enabling wider More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

delivery methodologies. SailPoint certification Identity Security Cloud Engineer, CISSP, CISM, or similar. Collaboration experience with MS Teams\Zoom collaboration. Identity AI adoption for risk-based access analytics and behavioural anomaly detection. Should this position be of interest please submit your CV and I will be in contact as required. More ❯

delivery methodologies. SailPoint certification Identity Security Cloud Engineer, CISSP, CISM, or similar. Collaboration experience with MS Teams\Zoom collaboration. Identity AI adoption for risk-based access analytics and behavioural anomaly detection. Should this position be of interest please submit your CV and I will be in contact as required. Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting More ❯

principles and statistical modeling. Day-to-day responsibilities include: Collaborate with other Data Scientists and Machine Learning Engineers to design and implement analytical approaches that inform scalable threat detection models. Partner with threat intelligence analysts to understand emerging attack techniques and leverage data to develop novel detection strategies and expose findings. Perform in-depth data analysis … to identify trends, relationships, and anomalies within vast security datasets. Develop, validate, and refine statistical and machine learning models for threat detection and intelligence generation. Monitor the performance of analytical models and threat intelligence pipelines, continuously identifying opportunities for improvement and refinement. Investigate and resolve data-related issues in production environments, ensuring the accuracy and integrity of our … to support your learning on the job, but prior experience is a plus: Experience with large-scale data processing frameworks (e.g., Spark, Flink). Experience with time series analysis, anomaly detection, or graph analytics in a security context. Proficiency in data visualization tools and techniques to effectively communicate complex findings. A basic understanding of the cyber threat More ❯