1 to 25 of 32 Remote/Hybrid Anomaly Detection Jobs in the UK excluding London

toxic combinations, identity exposure, control gaps, and vulnerability prioritization. Build and evaluate graph algorithms and ML models including centrality, community detection, similarity, anomaly detection, node classification, link prediction, embeddings, and Graph Neural Networks. Design GraphRAG and knowledge-grounded security assistants that combine graph traversal, vector … JanusGraph . Graph data science: Neo4j Graph Data Science, NetworkX , PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. Programming and engineering: Advanced Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers ...

Collaborate with engineering and business stakeholders to identify performance trends, operational opportunities, and actionable insights. Create data pipelines and workflows that support operational monitoring, anomaly detection, service analytics, and business intelligence initiatives. Integrate data from multiple enterprise systems including Azure, SQL databases, APIs, cloud platforms, and operational … Azure Data Factory, Synapse Analytics, Data Lake, or related cloud data technologies. Experience creating executive dashboards and operational reporting solutions. Knowledge of machine learning, anomaly detection, predictive analytics, or statistical analysis techniques. Experience working with large-scale telemetry, operational, or IoT datasets. Familiarity with DevOps practices ...

Collaborate with engineering and business stakeholders to identify performance trends, operational opportunities, and actionable insights. Create data pipelines and workflows that support operational monitoring, anomaly detection, service analytics, and business intelligence initiatives. Integrate data from multiple enterprise systems including Azure, SQL databases, APIs, cloud platforms, and operational … Azure Data Factory, Synapse Analytics, Data Lake, or related cloud data technologies. Experience creating executive dashboards and operational reporting solutions. Knowledge of machine learning, anomaly detection, predictive analytics, or statistical analysis techniques. Experience working with large-scale telemetry, operational, or IoT datasets. Familiarity with DevOps practices ...

should expect to join customers periodically and for technical discussions. Engineers who never meet the customer build the wrong thing. KEY RESPONSIBILITIES Take our anomaly detection work from proof of concept into production across the estate, moving from retrospective analysis to live early warning. Build the validation … stack. Hands‐on experience with time‐series, sensor or telemetry data at scale, including the realities of gaps, drift, flatlines and misbehaving devices. Applied anomaly detection or predictive modelling taken into production, with the judgement to keep methods robust and explainable rather than elaborate. Practical experience building ...

this role you will define and deliver next-generation finance capabilities that include predictive modelling, trend analysis, risk identification, automated insight generation, and faster anomaly detection across the business, Working closely with Finance, Accounting, Product and Technology stakeholders, you will translate complex business challenges into scalable digital … Define and own the product vision, roadmap, and success measures for AI-enabled finance technology products across financial management, predictive modelling, insight generation, and anomaly detection. Partner with Finance, Accounting, Product and Technology teams to identify high-value business problems and convert them into prioritised product outcomes, requirements ...

generation, fine-tuning, or prompt engineering Exposure to distributed data processing frameworks, such as Spark Exposure to fraud detection, anti-money laundering, anomaly detection, or graph and network-based modelling Awareness of model risk management, governance, and regulatory controls within financial services ...

libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

security of AI (protecting the organisation's own AI systems and use of AI) and AI for security (using AI to strengthen protection, detection and response). This role will sit within Cyber Security and Compliance. Technical ownership of AI security tool selection and deployment Define requirements … with stakeholders. In protection, that might mean AI-assisted vulnerability prioritisation, secure code review, or posture analysis. In detection, it covers behavioural anomaly detection, alert triage and enrichment, and LLM-assisted threat hunting. In response, it includes AI copilots for investigation and incident summarisation, automated ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

vaulting, and distributed secrets via external‐secrets patterns (e.g., AWS Secrets Manager, Azure Key Vault). Apply AI‐assisted tooling and analytics to improve anomaly detection, provisioning accuracy, and audit evidence of quality, while maintaining governance and data‐protection standards. Collaborate with engineering, operations, compliance, and security ...

applied within service management to improve operational efficiency, employee experience and service outcomes.* Awareness of modern AIOps and observability capabilities, including monitoring, event correlation, anomaly detection, intelligent alerting, operational analytics and automation.* Familiarity with enterprise service management platforms such as ServiceNow, Jira Service Management, Freshworks or similar ...

applied within service management to improve operational efficiency, employee experience and service outcomes.* Awareness of modern AIOps and observability capabilities, including monitoring, event correlation, anomaly detection, intelligent alerting, operational analytics and automation.* Familiarity with enterprise service management platforms such as ServiceNow, Jira Service Management, Freshworks or similar ...

software delivery lifecycle. Familiarity with OpenTelemetry, automation, Infrastructure as Code and modern engineering practices. Knowledge of AI-powered operations (AIOps), operational intelligence, event correlation, anomaly detection, and emerging AI capabilities within operations platforms. Ability to define how Generative AI, AI assistants and intelligent operational workflows can enhance ...

huge impact to the security of the UK. 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 ...

operational efficiency. Design and implement observability platforms to effectively monitor system health, performance, and reliability. Develop strategies for AI-driven alerting and proactive anomaly detection to reduce Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR). Establish and enforce SRE best practices, including Service ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights. ...

/4 and ecosystem applications (APIs, events, SLT/CDC, iPaaS/BTP). Prioritise AI use cases (forecasting, ATP optimisation, document AI, anomaly detection). Define ML data contracts and embed models in operational processes (Fiori, SAC). Establish MLOps foundations: pipelines, CI/CD, monitoring ...

projects and human resources. Communicate the value of Industrial AI, automation and intelligent workflows in improving finance and operational decision‐making, productivity, forecasting and anomaly detection. Work closely with Sales, Product Management, Presales and Consulting teams to progress opportunities and deliver value led customer engagements across the UK region. ...

points, digital adoption challenges, and operational inefficiencies. Provide clear, actionable recommendations. Advance AI-native analytics Use Gen AI tools for automated insight generation, summarisation, anomaly detection, and workflow optimisation. Support experimentation & continuous improvement Analyse A/B tests and digital experience performance, quantifying customer and business impact. ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights. ...

Site Reliability Engineering (SRE) maturity, embedding monitoring, observability, automated testing and structured incident response Drive adoption of automation and AI‐enabled tooling to improve anomaly detection, incident management, vulnerability management and operational efficiency Provide technical oversight of production operations, ensuring alignment between platform standards and operational support ...