1 to 25 of 63 Anomaly Detection Jobs in the UK excluding London

forward investment in AI-driven operations. Over the course of the first year, the organization intends to incorporate AIOps and ML-assisted observability — anomaly detection, intelligent alert correlation, LLM-assisted runbook generation — into how we monitor and respond to our platform. You will be the technical owner … equivalent). Validate that what we think is resilient actually is. AI-driven operations Architect Omnicell's AIOps direction: evaluate and introduce ML-based anomaly detection, predictive alerting, automated root cause analysis, and LLM-assisted runbook or triage pipelines. Make informed build-versus-buy calls across ...

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 … ArangoDB, or 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/ ...

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 ...

schema design and data storage, transformation/ETL, model training and evaluation, and operational delivery. Develop statistical and machine learning models for entity resolution, anomaly detection, classification, clustering, and pattern-of-life analysis across multi-INT datasets. Build dashboards and lightweight applications that communicate key insights, assessments … schema design and data storage, transformation/ETL, model training and evaluation, and operational delivery. Develop statistical and machine learning models for entity resolution, anomaly detection, classification, clustering, and pattern-of-life analysis across multi-INT datasets. Build dashboards and lightweight applications that communicate key insights, assessments ...

identify inefficiencies, yield losses, contamination risks and equipment deviations. • Improve chemometric models, including calibration development, validation and ongoing performance. • Explore time-series modelling, anomaly detection and advanced process optimisation techniques. • Help automate model development, maintenance and deployment workflows. • Work directly with customers to understand operational challenges, data … manufacturing or process industries. • Knowledge of chemometrics, including PLS, PCA, spectral preprocessing or calibration development. • Experience with spectroscopy or analytical instrumentation. • Time-series analytics, anomaly detection or industrial process optimisation. • Familiarity with Azure-based data and analytics environments. The Person We're Looking For We value potential ...

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 ...

Experience in insurance or other financial services. Experience with B2B, enterprise software, or complex customer implementations. Interest or experience in fraud detection, anomaly detection or other risk-related domains. Familiarity with agile product development methods and tools such as Jira, Confluence or equivalent. Qualifications ...

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 ...

real-world security challenges. The role Develop statistical models and unsupervised learning techniques to identify anomalies in complex datasets. Investigate data, evaluate different detection approaches and assess their effectiveness. Turn experimental work into robust, tested and maintainable production software. Contribute to architecture and technical decisions as the product … writing reliable, well-tested production code. Strong Python engineers with previous Java experience and solid engineering fundamentals will also be considered. Experience in cybersecurity, anomaly detection, fraud detection or behavioural analytics would be valuable, alongside exposure to ClickHouse or numerical and ML libraries. What ...

bridging operational systems and the analytical layer until IT takes full ownership. Develop and implement AI/ML-enabled data features — including data enrichment, anomaly detection, and predictive pipelines. Integrate AI APIs and LLM-based tools into data workflows to accelerate analytics at scale. Work closely with ...

decision-making. You will develop advanced analytical use cases across areas such as forecasting, revenue leakage, client churn, sales conversion, profitability, capacity and anomaly detection. You will balance analytical rigour with speed, keeping solutions understandable, actionable and focused on measurable business outcomes. You will work closely with Data Engineering ...

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 ...

prototype, and evaluate ML/AI techniques to support efficient, reliable observatory operations in areas such as observation scheduling, telescope and data quality monitoring, anomaly and RFI detection, and support for our user community. The successful candidate will be highly skilled in communication, as well … work both independently and collaboratively within a globally distributed team. Desirable Knowledge, Skills and Experience Experience applying ML/AI to time-series, imaging, anomaly detection, classification or optimisation problems. Familiarity with radio interferometric data and processing (e.g. visibilities, calibration, RFI flagging), or a willingness to learn ...

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 ...

data into actionable insights. Models may include predictions and forecasts, text analytics and Natural Language Processing (NLP), as well as unsupervised tasks such as anomaly detection Researching, proposing and prototyping ML models to demonstrate and provide business value to solve specific business problems Designing, developing and implementing ...

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 ...

Influence technical direction rather than simply execute a roadmap. Build solutions across the complete machine learning lifecycle. Develop expertise in cutting-edge areas including anomaly detection, agentic AI and intelligent decision-support systems. Operate in a high-trust environment with genuine ownership and accountability. Move faster, with ...

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 ...