1 to 25 of 36 Anomaly Detection Jobs in the UK

and network expansion. Partner with commercial and product stakeholders to embed data into every stage of the sales, account management, and network growth processes. Build models for customer segmentation, anomaly detection, forecasting, fraud/risk scoring, and identifying growth opportunities in existing and untapped markets. Turn data into actionable insights, proactively and persuasively translating data into meaning … drive decisions. Nice-to-Haves Experience with forecasting models for revenue, client growth, and network activity. Familiarity with data visualization tools like Tableau. Exposure to fraud detection, anomaly detection and pattern recognition modeling. Create a Job Alert Interested in building your career at Freemarket? Get future opportunities sent straight to your email. Apply for this More ❯

requirements for critical assets. Analyse and extend Dynatrace coverage across complex applications. Configure, optimise, and automate monitoring within the Dynatrace toolset. Provide AI-driven insights (via Davis AI) for anomaly detection, root cause analysis, and proactive recommendations. Support operational resilience by embedding observability standards and best practices. Engage in workshops with third-party suppliers to review and … improve observability standards. TECH STACK/REQUIREMENTS Strong expertise in Dynatrace (SaaS & On-Premises) including: Application Performance Monitoring Anomaly Detection Profiles Alerting Rules & Profiles Synthetic & Log Monitoring Real User Monitoring (RUM) DQL & Grail for advanced data analytics API integrations with complex systems Experience working in resilience/observability engineering. Strong communication skills and ability to work in More ❯

Defender, Microsoft Sentinel, and Google Chronicle, with a strong focus on playbook development, analytical rule creation, and threat modelling. You will be instrumental in building and optimizing our detection and response strategies. Job Duties SIEM Engineering & Management Deploy, configure, and maintain … SIEM platforms (Splunk, QRadar, Sentinel, Defender, Chronicle). Onboard and normalize log sources across cloud and on-prem environments. Develop and optimize analytical rules for threat detection, anomaly detection, and behavioural analysis. Skills Must be able to obtain SC Clearance or already hold SC clearance. SIEM Expertise: Hands-on experience with at least two of More ❯

runtime-isolated, reproducible models that are easy to deploy, monitor, and update without connectivity. Work closely with data scientists to define clear KPIs and success criteria-such as detection accuracy, latency, false positive/negative rates, explainability, and robustness-to determine what constitutes a production-grade, releasable model. Align model performance goals with the operational realities of the … and stakeholder management skills. Comfortable working in a fast-paced, iterative, and agile environment. Preferred Experience: Solid understanding of cyber security concepts such as threat detection, SIEM, anomaly detection, and incident response. Experience with tools for tracking ML models in production (e.g., MLflow). We encourage you to apply even if your experience is not More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

relationships between metrics and benchmarks. Develop robust Trend Identification models to analyse key metrics, understand evolving trends, and provide actionable insights (e.g., input to pricing, axes). Implement Outlier Detection algorithms to pinpoint unusual data points, enabling investigation of potential risks or opportunities, and build Scenario Planning tools to model the incremental impact of client activities and market … learning, preferably within the financial services industry and ideally within Equities Prime Finance. Demonstrated experience applying AI/ML techniques to complex business problems, focusing on time series analysis, anomaly detection, forecasting, or Natural Language Processing (NLP). Strong proficiency in Python/R and expertise with AI/ML libraries/frameworks (e.g., scikit-learn, TensorFlow More ❯

training using behavioural insights generation - Operational-level digital twins of NHS hospital environments. - Safety and behavioural detection at level crossings. - AI for safety of autonomous systems. - AI anomaly detection in operational technology. Synoptix also recognizes the value of the successful candidate maintaining clinical proficiency Key Skills Required: A nationally registered clinician (GMC, NMC, HCPC) with More ❯

training using behavioural insights generation - Operational-level digital twins of NHS hospital environments. - Safety and behavioural detection at level crossings. - AI for safety of autonomous systems. - AI anomaly detection in operational technology. Synoptix also recognizes the value of the successful candidate maintaining clinical proficiency Key Skills Required: A nationally registered clinician (GMC, NMC, HCPC) with More ❯

training using behavioural insights generation - Operational-level digital twins of NHS hospital environments. - Safety and behavioural detection at level crossings. - AI for safety of autonomous systems. - AI anomaly detection in operational technology. Synoptix also recognizes the value of the successful candidate maintaining clinical proficiency Key Skills Required: A nationally registered clinician (GMC, NMC, HCPC) with More ❯

analysis, or EA, with 5+ years in finance systems. Proven expertise with finance operating models and KPIs (EBITDA, NPV, DSO). Experience with AI/ML in finance (e.g., anomaly detection, predictive AR). Skills & Tools Deep knowledge of SaaS, PaaS, microservices, data analytics, and EA frameworks. Familiarity with IT governance, DevOps, agile methodologies, and financial modeling. More ❯

millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over More ❯

environments. You will work closely with experts in quantum sensing to develop quantum magnetometry technology that will solve pressing challenges in aeronautical positioning and navigation, geophysical surveying, and magnetic anomaly detection. A key focus of the role will be developing and implementing methods for removing magnetic and/or vibrational noise induced by the platform on which the quantum … a closely related discipline; Experience performing data analysis, algorithmic development, and/or digital signal processing in one or more of the following areas: magnetic and/or gravitational anomaly detection; airborne magnetic and/or gravitational surveying; magnetic navigation; magnetic signature and/or platform motional characterisation and management; magnetic and/or vibrational signal denoising More ❯

Hosting, Google IAM, Secret Manager Azure: Azure OpenAI, Azure App Services, Azure AD authentication Cybersecurity: CSP headers, XSS/CSRF protection, OAuth2 flows, JWT encryption Front-end logging for anomaly detection and audit trails Familiarity with OWASP guidelines and secure SDLC practices DevOps: GitHub Actions, Docker, Terraform, security scans in CI/CD (e.g., Snyk, Dependabot or More ❯

Hosting, Google IAM, Secret Manager Azure: Azure OpenAI, Azure App Services, Azure AD authentication Cybersecurity: CSP headers, XSS/CSRF protection, OAuth2 flows, JWT encryption Front-end logging for anomaly detection and audit trails Familiarity with OWASP guidelines and secure SDLC practices DevOps: GitHub Actions, Docker, Terraform, security scans in CI/CD (e.g., Snyk, Dependabot or More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

Analyze high-resolution battery data from field units and test environments Build pipelines to process, visualize, and extract trends that inform algorithmic performance Apply machine learning techniques to enhance anomaly detection and predictive maintenance Cross-functional Collaboration Interface with software, hardware, and compliance teams to drive integrated product development Participate in peer reviews and contribute to process More ❯

objective of the role is to lead a global team that coordinate exceptional Services response to major technology events (planned or unplanned), team responsibilities encompasses oversight of 24x7 service anomaly detection for over 90 critical end to end flows ensuring adherence to regulatory mandated Critical Business Services (CBS) and a heightened focus on a subset of Platinum More ❯