1 to 25 of 26 Anomaly Detection Jobs in London

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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. What You'll Bring: You will More ❯

applications - ideally GCP, Azure or AWS You have external or internal consulting experience You have knowledge of host hardening, auditing, logging and monitoring, network security, SEIM deployments, security analytics, anomaly detections, PKI You have proven implementation of cloud security models, particularly identity, network, and encryption You have demonstrated understanding of Microsoft security technologies and strategy You have program management More ❯

models that power live decision-making. What You'll Be Doing: Designing and deploying production-grade ML models that drive live decision-making. Applying computer vision Building fraud and anomaly detection models using geospatial and behavioural signals. Partnering with engineers to scale pipelines, compliance monitors, and detection systems. Leading scientific direction and mentoring other data More ❯

key business services. Utilize Splunk ES for security event monitoring and correlation searches. Automate tasks and integrate systems using Python, Shell, or Perl scripting. Perform root cause analysis and anomaly detection by analyzing complex log data. Requirements: 10+ years experience in observability, with deep expertise in Splunk, especially ITSI. Proficiency in Scripting (Shell/PowerShell/Python More ❯

high-growth environment. Key Responsibilities Develop and deploy computer vision models, with a focus on image classification and quality scoring Apply machine learning techniques such as supervised learning and anomaly detection to visual data problems Work with large-scale, complex image datasets to create production-ready solutions Collaborate cross-functionally to ensure models are effectively integrated and More ❯

suppliers to review observability standards. What You'll Need: * The ability to demonstrate your extensive experience in designing and configuring the following within Dynatrace: o Application performance monitoring o Anomaly detection profiles o Alerting rules and alert profiles o Synthetic monitoring o Log monitoring o Real User Monitoring (RUM) to capture and analyse end-user experience across More ❯

party software suppliers to review observability standards.What You'll Need:* The ability to demonstrate your extensive experience in designing and configuring the following within Dynatrace:o Application performance monitoringo Anomaly detection profileso Alerting rules and alert profileso Synthetic monitoringo Log monitoringo Real User Monitoring (RUM) to capture and analyse end-user experience across web and mobile applications.o More ❯

business needs into data-driven solutions Essential skills: Python (pandas, NumPy, scikit-learn) – data wrangling, modelling, feature engineering SQL – querying structured datasets Model Development & Validation – classification, unsupervised learning (outlier detection), ranking models ML Deployment – containerised deployments (Podman, SageMaker, DSW pipelines) Git – version control for reproducible workflows Time-Series Analysis – spotting risk trends over time EDA – identifying early risk … signals and clusters Desirable skills: Rank aggregation/ensemble methods (e.g. Robust Rank Fusion) Model explainability tools (SHAP, LIME) Model monitoring & drift detection Experience in RegTech, FinCrime, or data-led supervision projects Please submit your CV, highlighting relevant experience. More ❯