1 to 25 of 56 Anomaly Detection Jobs in the UK excluding London

and maintain scalable, modular pipelines using AWS services (Glue, Lambda, Step Functions, S3), supporting ingestion, transformation, and storage across key business domains. Data Quality & Governance: Implement automated data validation, anomaly detection, lineage, and auditability; enforce consistent naming, access controls, and compliance with GDPR and healthcare standards. Performance & Cost Optimisation: Tune pipelines and query layers (Glue, Athena) for More ❯

and maintain scalable, modular pipelines using AWS services (Glue, Lambda, Step Functions, S3), supporting ingestion, transformation, and storage across key business domains. Data Quality & Governance: Implement automated data validation, anomaly detection, lineage, and auditability; enforce consistent naming, access controls, and compliance with GDPR and healthcare standards. Performance & Cost Optimisation: Tune pipelines and query layers (Glue, Athena) for More ❯

clean, reliable, query-ready datasets used by commercial, operational, and marketing teams. Defining and evolving the data architecture to support scale, cost-efficiency, and data quality. Building validation layers, anomaly detection, and alerting to ensure trustworthy, production-grade pipelines . Working with infrastructure-as-code tools (e.g. CDK, Terraform) to manage data infrastructure securely and repeatably. Driving More ❯

scalable, agnostic testing frameworks for use across agile delivery teams. Promote best practices including Test-Driven Development (TDD) , Behaviour-Driven Development (BDD) , and AI/ML-based testing for anomaly detection and performance validation. Mentor and upskill test and engineering teams in modern, automation-first testing approaches. Collaborate across teams to ensure quality and consistency throughout the More ❯

of different data sources into our Lakehouse (Databricks on Azure Data Lake) and its architecture. Be responsible for the reliability and quality of data in the Data Lake (including anomaly detection, data quality checks, reconciliations, access, permission, and retention management, PII treatment, and back-up/restoration plans). Set up and manage platform technologies to support More ❯

design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas such as … on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and … AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency in Python and More ❯

design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas such as … on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and … AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency in Python and More ❯

deliver data science developments, and actively participating in hiring to build a robust data science team. The role may involve expertise in either machine learning (e.g., predictive modelling, classification, anomaly detection) or mathematical optimisation (e.g., scheduling, resource allocation, route optimisation). Candidates with a strong background in one area and interest in the other are encouraged to More ❯

deliver data science developments, and actively participating in hiring to build a robust data science team. The role may involve expertise in either machine learning (e.g., predictive modelling, classification, anomaly detection) or mathematical optimisation (e.g., scheduling, resource allocation, route optimisation). Candidates with a strong background in one area and interest in the other are encouraged to More ❯

deliver data science developments, and actively participating in hiring to build a robust data science team. The role may involve expertise in either machine learning (e.g., predictive modelling, classification, anomaly detection) or mathematical optimisation (e.g., scheduling, resource allocation, route optimisation). Candidates with a strong background in one area and interest in the other are encouraged to More ❯

Microsoft Entra ID (Azure AD), SailPoint, ForgeRock, Okta. Familiarity with identity lifecycle management, privileged access management (PAM), and access certification processes. Understanding of event-driven data, behavioral analytics, and anomaly detection methods. Domain Knowledge: Basic understanding of digital identity concepts: SSO, MFA, RBAC and ABAC Knowledge of fraud detection techniques and identity risk indicators is More ❯

used by the team for various purposes such as training models or evaluating feature performance. These will need to be quality assured, well documented and with sufficient observability for anomaly detection in the underlying data. To build these datasets, it may be necessary to collect requirements from product, engineering or data science. Contributing to the definition of More ❯

making across the organization. You’ll be responsible for analysing complex datasets, building predictive models, and deploying scalable data solutions using cutting-edge technologies. Responsibilities • Create, test, and implement anomaly detection algorithms and prediction models for early problem identification and failure avoidance in safety-critical equipment. • Work with operational datasets such as maintenance logs and time-series More ❯

NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection techniques, algorithms, and applications. Excellent problem-solving, communication (verbal and written), and teamwork skills. Preferred qualifications, capabilities, and skills Experience with big data frameworks, with a More ❯

and efficiency. Leverage AWS technologies (S3, Athena, QuickSight) to analyse data from millions of field devices, delivering insights to inform decision-making and drive operational efficiency. Develop and implement anomaly detection techniques and data-driven solutions to proactively identify and resolve system issues. Perform global metric comparisons across various device models. Lead teams, mentor colleagues, and communicate More ❯

collaboratively with internal and external teams to identify opportunities for security improvements and review products that can advance our security capabilities, such as tools that support analysis/detection and other emerging technologies. Gather forensic data and physical equipment, to perform in-depth root cause analysis. Support use case tuning through auditing and approval, alongside developing new detection … security technologies, such as IDS, Web content filters, AV, SIEM, Vulnerability Management, Firewalls, and awareness of their purpose in a layered security approach alongside analysing their outputs for security anomaly detection. In-depth understanding of the cyber threat landscape, advanced adversary tactics, and the MITRE Attack Framework. Strong understanding of low-level concepts including operating systems, Active Directory, Windows More ❯

of-the-art NLP models, Transformers, Agentic Approaches for mixed (temporal and text) data analysis and summarization; Experience with pipeline orchestration tools like Airflow, Argo, etc.; Proven Experience with Anomaly Detection and Forecasting with explainability for temporal and mixed data; Intermediate+ English — ability to participate in written discussions with international teams and clients. Join a mission-driven More ❯

improvements and delivering them Be a point of contact for intrusion analysis, forensics and Incident Response queries. Able to provide root cause analysis of non-standard analytic findings and anomaly detections for which a playbook does not yet exist. Responsible for ensuring that during times of reduced capacity that all ADHOC and regular products are completed and are at … used within the Cyber Threat Intelligence Domain, Including the Cyber Kill Chain and MITRE ATT&CK Development of new analytics and playbooks that result in creation of new detection rules/analytics Requirements Technical 3+ years’ experience in Cyber Threat Intelligence, and conducting research and investigating cyber threats in a technical capacity Experience in technical incident response and More ❯

of Excellence to align data governance, quality, and reporting frameworks AI & Automation Enablement Build and scale a team focused on AI-led operational transformation (e.g. predictive analytics, smart routing, anomaly detection) Partner with data science and engineering teams to embed AI into service delivery workflows and client experience journeys Ensure all AI use cases meet compliance, governance More ❯

of Excellence to align data governance, quality, and reporting frameworks AI & Automation Enablement Build and scale a team focused on AI-led operational transformation (e.g. predictive analytics, smart routing, anomaly detection) Partner with data science and engineering teams to embed AI into service delivery workflows and client experience journeys Ensure all AI use cases meet compliance, governance More ❯

improvements and delivering them Be a point of contact for intrusion analysis, forensics and Incident Response queries. Able to provide root cause analysis of non-standard analytic findings and anomaly detections for which a playbook does not yet exist. Responsible for ensuring that during times of reduced capacity that all ADHOC and regular products are completed and are at … used within the Cyber Threat Intelligence Domain, Including the Cyber Kill Chain and MITRE ATT&CK Development of new analytics and playbooks that result in creation of new detection rules/analytics Requirements Technical 3+ years' experience in Cyber Threat Intelligence, and conducting research and investigating cyber threats in a technical capacity Experience in technical incident response and More ❯

business requirements, developing and reviewing conceptual and logical data models, troubleshooting and resolving model-related issues. Demonstrable expertise in analytics modelling: Predictive analytics, trend and correlation analysis, forecasting, outlier detection and exception reporting. Proven experience partnering effectively with senior business leaders. Proficient in data visualisation tools such as Power BI but experience of other tools welcome. Prior experience More ❯

Requirements • Experience in identifying opportunities for product or business improvements and measuring the success of those initiatives. • Experience in applying modelling techniques e.g. time series forecasting, segmentation/clustering, anomaly detection. If this great opportunity interests you, please make an application to our Recruitment Partner, Datatech Analytics More ❯

tailored security solutions that keep them resilient and secure. The Role We are seeking a Security Analyst to join our team and play a key role in threat detection, incident response, and security monitoring. The ideal candidate will have a strong analytical mindset, an understanding of cyber threats and attack techniques, and the ability to implement effective security … up to date with emerging threats, attack techniques, and security technologies . You are proactive, adaptable, and always looking for ways to improve security operations. Key Responsibilities Threat Detection & Security Monitoring Continuously monitor SIEM … IDS/IPS, firewalls, and endpoint security tools to identify suspicious activity. Analyze and correlate security alerts to detect potential cyber threats and data breaches. Perform log analysis and anomaly detection to identify patterns indicative of compromise. Incident Response & Threat Investigation Investigate security incidents, phishing attempts, malware infections, and unauthorized access events. Develop and implement remediation strategies More ❯

will contribute to the development of advanced machine learning models that support a broad spectrum of defence applications, including real-time object detection, multi-sensor data fusion, anomaly detection in complex systems, and predictive analytics for operational readiness. The role sits within a multidisciplinary engineering team, collaborating closely with software developers, data scientists, and subject More ❯