1 to 25 of 37 Anomaly Detection Jobs in the UK

Scotland - United Kingdom Type: Permanent Senior SOC Engineer A leading organisation is seeking a Senior SOC Engineer to strengthen its security operations capability and drive continuous improvement across detection, response, and automation. This pivotal role requires deep expertise in IBM QRadar, with a strong focus on playbook development, analytical rule creation, and threat modelling. The Senior SOC Engineer … will play a key role in building and optimising detection and response strategies, ensuring robust protection against evolving threats. Key Responsibilities SIEM Engineering & Management … Deploy, configure, and maintain the QRadar SIEM platform. Onboard and normalise log sources across on-premises and cloud environments. Develop and optimise analytical rules for threat detection, anomaly detection, and behavioural analysis. Playbook Development & Automation Design and implement incident response playbooks for scenarios such as phishing, lateral movement, and data exfiltration. Integrate playbooks with SOAR More ❯

of rough path theory and modern machine learning. This ambitious, multi-institutional collaboration aims to redefine how streamed data is modelled and processed-unlocking new capabilities in generative AI, anomaly detection, and real-time decision-making. What you would be doing Key scientific challenges you'll help tackle: Next-generation Transformers: Develop mathematically grounded architectures for continuous … multimodal data streams. Efficient Representations: Create robust, interpretable, and scalable representations using signature and path development techniques Anomaly Detection: Build principled, representation-invariant methods for identifying outliers in high-dimensional data with use in appllications. The postholders will be expected to make significant contributions to the mathematical foundations of the programme, engage actively with the broader DataSıg More ❯

deliver enduring solutions. What You'll DoYou will serve as Kubrick's technical authority on the design, development, and deployment of supply chain solutions (e.g. supply chain optimisation, simulation, anomaly detection, and forecasting).Demonstrating domain expertise across key supply chain functions, including Planning, Procurement, Manufacturing, and Logistics, you will hold a strong understanding of their interdependencies and … defining best practices for supply chains, ensuring scalability, reliability, security, cost-efficiency, and ethical design.Required Skills and ExperienceTechnical•Deep understanding of supply chain solutions (e.g. supply chain optimisation, simulation, anomaly detection, and forecasting).•Proven experience designing and deploying solutions in production environments.•Strong grasp of systems thinking and distributed architectures integrating AI and enterprise platforms.•Proficiency More ❯

join our success story! As our Technical Lead for the AWS Engineering team, you will be responsible for:- Leading the design, development, and deployment of a bespoke fraud detection and transaction monitoring system. Collaborating with a variety of stakeholders and financial crime experts globally to define a technical vision and strategy for the platform. Architecting scalable and robust … and third-party tools. Ensuring high code quality and engineering best practices through code reviews, mentoring, and technical guidance. Owning and evolving the technical design of core fraud detection components. Driving continuous improvement in team processes, tooling, and development workflows. Coaching and supporting engineers in their technical growth, fostering a culture of learning and continuous improvement. Providing thoughtful … automation) TypeScript and React (frontend development) Excellent communication and stakeholder management skills. Demonstrated expertise in technical design and architecture of distributed systems. Familiarity with fraud detection models, anomaly detection, and rule-based systems. Clear understanding of secure coding practices and data privacy principles. Exposure to CI/CD pipelines and infrastructure-as-code tools (e.g. More ❯

join our success story! As our Technical Lead for the AWS Engineering team, you will be responsible for:- Leading the design, development, and deployment of a bespoke fraud detection and transaction monitoring system. Collaborating with a variety of stakeholders and financial crime experts globally to define a technical vision and strategy for the platform. Architecting scalable and robust … and third-party tools. Ensuring high code quality and engineering best practices through code reviews, mentoring, and technical guidance. Owning and evolving the technical design of core fraud detection components. Driving continuous improvement in team processes, tooling, and development workflows. Coaching and supporting engineers in their technical growth, fostering a culture of learning and continuous improvement. Providing thoughtful … automation) TypeScript and React?(frontend development) Excellent communication and stakeholder management skills. Demonstrated expertise in technical design and architecture of distributed systems. Familiarity with fraud detection models, anomaly detection, and rule-based systems. Clear understanding of secure coding practices and data privacy principles. Exposure to CI/CD pipelines and infrastructure-as-code tools (e.g. More ❯

and billions of transactions annually. Leveraging proven data science, including our proprietary consortium data, our customers use our risk-based, machine learning platform to deliver the highest fraud detection rates, lowest false positive rates, and lowest customer intervention in the industry. We stop fraud, not customers. See what others can't at What you'll achieve As a … analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Qualifications Bachelor's degree in Data Science, Computer Science, or a related field. Doctorate in a … of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is a major advantage. Advanced proficiency in Python for data science and machine learning applications. Familiarity with cloud-based infrastructure, preferably Azure. Expertise with Data Warehousing/ More ❯

with governed datasets and internal tools. Build lightweight portals, scripts, and APIs to streamline business workflows. AI & Advanced Analytics Integrate AI services into BI dashboards and operational workflows (e.g., anomaly detection, natural language Q&A). Implement semantic search and intelligent alerting using AWS Bedrock or Azure equivalents. Security, Governance & Resilience Enforce least-privilege access, RBAC, and More ❯

access controls, and auditing). Collaborate with finance and data teams to define data models, schemas, and governance policies that support modern finance workflows, including automated reporting, forecasting, and anomaly detection. Implement data retrieval mechanisms optimized for LLM-based querying via Co-pilot and/or similar tools, enabling natural language access to financial data while maintaining accuracy and More ❯

completeness, timeliness, and consistency across systems. Utilise Monte Carlo for data observability, proactively detecting and resolving data quality issues. Work with data engineering teams to establish validation, profiling, and anomaly detection frameworks. Stakeholder Engagement & Support Act as a bridge between business and technical teams, ensuring alignment of data requirements. Provide training and guidance to business users on More ❯

scalability, and reliability. Utilise tools like Alteryx for data transformation and cleansing to improve workflow efficiency. Data Innovation & Automation: Apply AI tools and automation to enhance reporting capabilities, including anomaly detection and performance forecasting. Support the integration of predictive analytics and natural language query tools to facilitate self-serve data access. Enablement & Stakeholder Engagement: Partner with key 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 ❯

with drone software stacks (e.g. ArduPilot, PX4). Experience with telemetry protocols like MAVLink. Awareness of cybersecurity practices in distributed systems. Exposure to machine learning in robotics, optimisation, or anomaly detection. Experience in safety-critical or high-reliability systems engineering. Knowledge of containerisation and cloud deployment (Docker, Kubernetes, AWS/GCP). What We Offer The opportunity to work More ❯

with drone software stacks (e.g. ArduPilot, PX4). Experience with telemetry protocols like MAVLink. Awareness of cybersecurity practices in distributed systems. Exposure to machine learning in robotics, optimisation, or anomaly detection. Experience in safety-critical or high-reliability systems engineering. Knowledge of containerisation and cloud deployment (Docker, Kubernetes, AWS/GCP). What We Offer The opportunity to work More ❯

with drone software stacks (e.g. ArduPilot, PX4). Experience with telemetry protocols like MAVLink. Awareness of cybersecurity practices in distributed systems. Exposure to machine learning in robotics, optimisation, or anomaly detection. Experience in safety-critical or high-reliability systems engineering. Knowledge of containerisation and cloud deployment (Docker, Kubernetes, AWS/GCP). What We Offer The opportunity to work More ❯

and investment planning. Knowledge of KPIs and ability to architect solutions that improve financial and operational performance. Exposure to AI/ML use cases in corporate functions (e.g. finance anomaly detection, HR attrition modelling, procurement spend analytics) Job Offer Competitive salary of £100,000 to £130,000 per annum. Bonus target of 18% to reward performance. Private More ❯

data governance platforms Provide technical guidance and best practices for data profiling, cleansing, and validation Explore and apply AI-driven techniques (e.g., GenAI) to enhance data quality automation and anomaly detection. 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 ❯

energy clients to manage fleets of autonomous systems and turn vast inspection data into actionable intelligence. Our platform is becoming the mission control for critical infrastructure monitoring, combining dashboards, anomaly detection, rules/alerts, and predictive analytics into one solution. Already working with some of the world s leading industrial organisations, this platform is central to our More ❯

energy clients to manage fleets of autonomous systems and turn vast inspection data into actionable intelligence. Our platform is becoming the “mission control” for critical infrastructure monitoring, combining dashboards, anomaly detection, rules/alerts, and predictive analytics into one solution. Already working with some of the world’s leading industrial organisations, this platform is central to our 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 ❯