26 to 50 of 178 Anomaly Detection Jobs in England

identify opportunities for analysis, modelling or product use. Develop, compare and validate appropriate statistical and machine-learning models for classification, ranking, recommendation, forecasting, anomaly detection, similarity or extraction problems. Use NLP, embeddings and LLM-assisted techniques responsibly for classification, entity resolution, information extraction, clustering and relationship discovery ...

meet evolving analytical and business requirements. Drive high standards of data quality, integrity and governance through the implementation of automated validation, cleansing, monitoring and anomaly detection processes. Integrate, transform and harmonise data from a wide range of internal and external sources, including policy, claims, telematics and third ...

from development into production environments. Python and associated data science ecosystem (Pandas, NumPy, Scikit‐learn). Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent‐based AI solutions. SQL and large‐scale data analysis. Cloud‐based data science platforms ...

Enterprise Solutions, shaping high-rigor analytical capabilities across a complex, regulated global financial-services environment. Design, build, and operate production-grade models for anomaly detection, variance analysis, drift detection, forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready. ...

licence optimisation, hardware rightsizing, capacity rebalancing, decommissioning, and vendor renegotiation Cost Governance Gaps — Assess and strengthen cost governance processes including approval workflows, budget controls, anomaly detection, and policy enforcement Data Normalisation — Normalise cost data from disparate sources into a unified cost model, enabling consistent reporting across business … months) based on value and feasibility Reporting & Dashboards — Design and recommend live/near‐real‐time cost dashboards with drill‐down capabilities, trend analysis, anomaly alerts, and executive reporting views FINOPS PERSONA COLLABORATION Executives (CTO, CFO, CIO) — Present cost visibility dashboards, business cases for optimisation, and FinOps maturity roadmaps ...

Effective collaboration within multidisciplinary teams, supported by strong problem-solving, documentation and critical-thinking skills.**Desirable Skills & Experience*** Advanced statistical modelling, experimental design, forecasting, anomaly detection, model optimisation or explainability.* Deployment and operation of machine-learning models, including monitoring, drift detection and performance management.* Awareness ...

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 ...

services. Establish self-service data quality capabilities, monitoring frameworks, observability solutions, and quality controls across critical enterprise data assets Enable proactive data profiling, anomaly detection, root cause analysis, and issue management capabilities. Partner with Data Engineering and Data Product teams to embed quality controls throughout the data ...

collaboration within multidisciplinary teams, supported by strong problem-s solving, documentation and critical-thinking skills. Desirable Skills & Experience Advanced statistical modelling, experimental design, forecasting, anomaly detection, model optimisation or explainability. Deployment and operation of machine-learning models, including monitoring, drift detection and performance management. Awareness ...

services, banking, wealth management, aviation, telecoms, public sector, or other regulated industries. Experience with enterprise document intelligence, knowledge graph systems, forecasting platforms, threat intelligence, anomaly detection, or AI-assisted decision systems. Background in designing reusable AI reference architectures and platform patterns. Why This Role This ...

data cataloguing, master data management and enterprise data-quality frameworks. Machine learning and advanced analytics: Experience applying analytical or AI techniques to data quality, anomaly detection or operational automation Cost Optimization: Understanding of Fabric capacity management and cost-efficient solution design. WHAT SUCCESS LOOKS LIKE Synapse workloads ...

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 ...

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 ...

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 ...

needs to act early Apply statistical and machine‐learning techniques to spot unusual data patterns, including issues that may otherwise go unnoticed Automate detection, alerting and safe recovery of common issues, and give the wider team the tools to investigate and fix problems themselves Trace how data … with Cyber Security and Infrastructure data, such as ServiceNow, Entra ID and Active Directory Applying machine learning or AI to operational problems, such as anomaly detection AI‐assisted development with tools such as GitHub Copilot and Claude Code Streamlit and Power BI A Snowflake or architecture certification ...

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 ...

reuse. Schedule, monitor, and manage data pipelines using Airflow or similar workflow orchestration tools to ensure reliable, timely data delivery. Implement validation, reconciliation, and anomaly-detection controls to maintain data completeness, accuracy, and consistency. Apply AI to automate schema inference across structured and semi-structured data sources ...

data structures that abstract technical complexity from business users. Help evolve the practice from static report production toward AI-augmented insight, such as automated anomaly detection, forecasting, and plain-language explanation of results. Enforce review and validation standards for AI-assisted development and AI-generated insights ...

models, ensuring business definitions and relationships are consistently represented in the engineered data products. Apply AI across data engineering, from data quality monitoring and anomaly detection to automated documentation and AI-assisted code, with appropriate human oversight. Simplify the estate and retire legacy platforms: lead the technical ...

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 ...

especially Java. Demonstrable experience collaborating with engineering on services Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL) Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis Experience with statistical analysis and good presentation skills to drive insight … Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, CI/CD Prior experience in the fraud domain and a strong understanding of fraud detection techniques Experience designing and deploying LLM-based solutions in production We’re people without borders — without judgement or prejudice, too. We want to work ...

especially Java. Demonstrable experience collaborating with engineering on services Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL) Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis Experience with statistical analysis and good presentation skills to drive insight … Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, CI/CD Prior experience in the fraud domain and a strong understanding of fraud detection techniques Experience designing and deploying LLM-based solutions in production We’re people without borders — without judgement or prejudice, too. We want to work ...

churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning. Optimization: Building engines for marketing spend, inventory management, or resource allocation. Causal ...