76 to 100 of 123 Anomaly Detection Jobs in London

exposure. Improve insight into technology currency, CMDB health, asset lifecycle, software and SaaS optimisation, cloud economics, risk and control effectiveness. Introduce predictive analytics, automation, anomaly detection and responsible AI‐enabled decision support. Replace manual and fragmented reporting with governed, repeatable and traceable analytical products. Partner with technology ...

/Service/Marketing Cloud, integrations, or Apex best practices). Experience applying AI/ML in engineering workflows (e.g., coding assistants, test generation, anomaly detection, intelligent routing) or product features. Background in leading distributed teams and large‐scale refactoring or platform modernisation initiatives. Key Behaviours & Attributes ...

involved in. Payments Initiation Modernization - Help a major global bank modernize the technology behind payments initiation to improve performance, implement intelligent monitoring and anomaly detection, and strengthen platform support. Cross-Border Payments Migration - Support a major global bank in migrating cross-border payments processing to a strategic ...

involved in. Payments Initiation Modernization - Help a major global bank modernize the technology behind payments initiation to improve performance, implement intelligent monitoring and anomaly detection, and strengthen platform support. Cross-Border Payments Migration - Support a major global bank in migrating cross-border payments processing to a strategic ...

solve complex problems and drive business outcomes; Research, develop, and implement machine learning algorithms and models for tasks such as classification, regression, clustering, anomaly detection, and recommendation systems; Research, develop, and implement AI tools such as NLP, LLM, and IA; Collect, preprocess, and curate large datasets required ...

evaluators and benchmarks for forecasting and other time-series tasks. Push the frontier of Timestral: architectures, training recipes, scaling, and new capabilities such as anomaly detection, classification and embeddings. Fine-tune and adapt Timestral on client data, in the cloud or on-premise, and benchmark it against ...

operators who use the agents. What you'll do Classical ML Build models. Classification and ranking for lead quality and traffic performance, anomaly detection, and forecasting. Evaluate and monitor them. Sound validation offline, drift checks once live, working with our platform team, who run model deployment ...

canary releases, blue/green deployments, feature flags or chaos/game days. Experience developing AI-assisted operations capabilities, such as alert enrichment, anomaly detection, triage support or runbook automation. Reliability engineering: SLOs, SLIs, error budgets, incident reduction and service health. Production excellence: monitoring, alerting, observability, runbooks ...

pipeline works like clockwork. Improve and support its complex infrastructure. ML Experience: Practical experience with ML, including classification, clustering, time series forecasting, and anomaly detection. You need to know the concept and be handy with the most common libraries Model Hosting and Monitoring: Host and monitor NLP models ...

. Working knowledge of Python or a similar scripting language for data analysis. Basic understanding of data analytics and statistics, including trend analysis and anomaly detection. Ability to interpret process diagrams and technical documentation (PFDs, P&IDs, equipment data). Exposure to industrial or operational data systems (e.g., historians ...

APIs. AI Innovation: Identify and implement high-impact opportunities for embedding GenAI and Agentic Workflows into IT Operations for alert analysis, remediation, and data anomaly detection. Governance & Health: Oversee CMDB health maintenance, data normalization, and reconciliation processes to ensure a "self-healing" IT environment. Collaborate: Act as a bridge ...

outcomes. Incident Management & Response Lead response activities relating to scraping, automated abuse, enumeration and traffic-related incidents. Maintain operational playbooks and runbooks for detection, escalation, mitigation and recovery. Implement controls using staged rollout approaches, balancing risk reduction with customer impact. Monitor effectiveness of controls and continually improve protection … Review recent incidents and identify immediate improvement opportunities. Begin establishing operational playbooks and governance processes. By 3-6 Months Establish repeatable workflows for traffic anomaly detection and response. Create clear ownership and decision-making processes for content protection activities. Reduce engineering involvement in reactive mitigation activities. Deliver ...

browser automation frameworks Strong knowledge of HTML parsing, DOM traversal, and data extraction techniques Experience handling rate limiting, CAPTCHA, IP rotation, and bot detection systems Comfortable working with asynchronous and concurrent scraping architectures Experience running scrapers at scale in cloud environments Strong debugging skills and ability to reason … Familiarity with containerisation and orchestration, such as Docker and Kubernetes Experience with distributed task systems and job queues Background in data quality monitoring and anomaly detection Experience working with search, advertising, or competitive intelligence data What We Value Pragmatic problem-solving in hostile and fast-changing technical ...

Build processing pipelines that take ranging data from raw returns to normal points and higher-level products Develop statistical methods for bias detection, outlier rejection and data quality Analyse station and network performance, and find where it can improve Work with our geodesy and orbit determination team … writing production code, not just notebooks Nice to have SLR or GNSS data, including the CRD format Cloud data pipelines Machine learning for anomaly detection What We Offer A high-impact role with real ownership at an early-stage, venture-backed spacetech company EMI share options ...

Build instrumentation libraries, SDKs, and eBPF-based auto-instrumentation to emit high-quality telemetry, with and without code changes Reduce mean time to detection and resolution by building cross-signal correlation—from kernel-level events up to application traces—unified query interfaces, and AI-assisted diagnostic tooling Drive … OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting The annual compensation range for this role is listed below. For sales roles, the range provided ...

decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms ...

points, digital adoption challenges, and operational inefficiencies. Provide clear, actionable recommendations. Advance AI-native analytics Use Gen AI tools for automated insight generation, summarisation, anomaly detection, and workflow optimisation. Support experimentation & continuous improvement Analyse A/B tests and digital experience performance, quantifying customer and business impact. ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights. ...

Linux shell experience, and proficiency with Python, Bash, and automation tools such as Ansible Experience applying AI/ML tools to network performance optimization, anomaly detection, and predictive analytics, with an understanding of frameworks such as TensorFlow, PyTorch, and scikit‐learn Experience using telemetry and observability frameworks ...

frameworks, and tooling, with the ability to apply them pragmatically in line with client needs.Understands where AI meaningfully enhances backend systems (e.g., classification, summarisation, anomaly detection) versus where traditional algorithms are more appropriate.Consulting & Client DeliveryExperience working in a consulting or client-facing environment, comfortable operating in ambiguous ...

committed. Provide feedback on AI model outputs to support continuous improvement of match accuracy, classification quality, and enrichment relevance. Work with AI-driven anomaly detection alerts, investigating flagged records and determining appropriate stewardship actions. Data quality monitoring and remediation Monitor data quality dashboards and alerts, investigating exceptions ...

projects. Familiarity with industrial automation systems (e.g., DCS, PLC, OPC, historian systems). Understanding of AI/ML applications in process control (forecasting, optimisation, anomaly detection) is a plus. Comfortable collaborating with operators, engineers, and data scientists — bridging industrial know‐how with data‐driven insights. Analytical ...

platform integration issues within monitoring environments while supporting ITIL-aligned incident management processes. Practical knowledge deploying OneAgent/ActiveGate components plus configuring alerting policies anomaly detection rules dashboards custom reporting. Experience integrating Dynatrace with ServiceNow or equivalent ITSM platforms using APIs for administration reporting automation. Working knowledge ...

scale, including REST, OData,GraphQL, and webhook/event patterns into ERP-class systems What sets candidates apart Classical ML depth alongside GenAI: forecasting, anomaly detection,predicTherole This is a hands‐on architect role that grows into a player‐coach role. You will start as the senior ...

cybersecurity threat detection that scales across billions of events and integrates with analysts’ workflows. You will build analyst dashboards, ML models for anomaly detection and threat classification, and data pipelines for real-time ML insights. Expect collaboration with security researchers and fast iteration ...