1 to 25 of 35 Permanent Anomaly Detection Jobs in London

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

insight for operators and leadership - not dashboards that nobody reads, but conclusions that change decisions – Put AI tooling to work on analysis, reconciliation, and anomaly-spotting at scale Inbound Data Quality – Own QA on inbound data from newly acquired companies - profiling, reconciliation, validation against source, anomaly detection … spreadsheets at a high level; comfortable interrogating and reconciling data rather than taking it on trust – Experience doing real data QA - profiling, validation, reconciliation, anomaly detection - with an instinct for where data goes wrong – Comfortable partnering with engineering on internal tooling: metric definition, requirements, output validation – Resourceful ...

insight for operators and leadership - not dashboards that nobody reads, but conclusions that change decisions – Put AI tooling to work on analysis, reconciliation, and anomaly-spotting at scale Inbound Data Quality – Own QA on inbound data from newly acquired companies - profiling, reconciliation, validation against source, anomaly detection … spreadsheets at a high level; comfortable interrogating and reconciling data rather than taking it on trust – Experience doing real data QA - profiling, validation, reconciliation, anomaly detection - with an instinct for where data goes wrong – Comfortable partnering with engineering on internal tooling: metric definition, requirements, output validation – Resourceful ...

insight for operators and leadership - not dashboards that nobody reads, but conclusions that change decisions – Put AI tooling to work on analysis, reconciliation, and anomaly-spotting at scale Inbound Data Quality – Own QA on inbound data from newly acquired companies - profiling, reconciliation, validation against source, anomaly detection … spreadsheets at a high level; comfortable interrogating and reconciling data rather than taking it on trust – Experience doing real data QA - profiling, validation, reconciliation, anomaly detection - with an instinct for where data goes wrong – Comfortable partnering with engineering on internal tooling: metric definition, requirements, output validation – Resourceful ...

Role We are seeking a Data Scientist to work on advanced analytical solutions across biometric and geospatial (GPS) datasets, with a particular focus on anomaly detection. You will work with multiple complex data streams, including biometric data captured via wearable technologies and location-based datasets. This role will suit … technical direction in a fast-paced, evolving environment with minimal structure. Key Responsibilities Develop and deploy data science models, with a focus on anomaly detection Work across multiple datasets, including biometric and GPS/location data Analyse and interpret data generated from wearable hardware devices Collaborate with ...

goes next, what we retire, and what we keep. Treat the network as a system that learns. Drive the use of AI in operations: anomaly detection across flow and streaming telemetry, predictive failure analysis on optical and routing layers, automated triage and runbook execution, traffic‐engineering … billing integrations. Enough to debug jointly with the Systems team, not to own the stack. Exposure to applying ML or AI in network operations (anomaly detection on telemetry, predictive failure analysis, automated remediation, model‐informed traffic engineering). We're not looking for a researcher ...

/ELT pipelines, microservices and service mesh topologies. Champion AI, ML and agentic automation opportunities within the trading technology estate including intelligent scheduling, anomaly detection, automated P&L attribution, predictive maintenance and agentic workflow orchestration (e.g., AWS AgentCore). Define and govern DevOps, platform engineering and observability ...

analytics, model risk governance, and regulatory expectations for pricing/risk models. Hands-on ML/AI for quant finance (signal extraction, surrogate modeling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimization, hedging algorithms, execution analytics, and transaction cost modeling. Familiarity with distributed ...

human identity sprawl. Ensure strong monitoring, alerting, and telemetry for IAM services and integrations, and partner with SecOps where needed (SIEM, logging, anomaly detection). Drive reduction in repeat incidents through disciplined root cause analysis, prevention, and engineering partnership. Build strong partnerships across Security, Infrastructure, HR, application ...

analytics, model risk governance, and regulatory expectations for pricing/risk models. Hands‐on ML/AI for quant finance (signal extraction, surrogate modelling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimisation, hedging algorithms, execution analytics, and transaction cost modelling. Familiarity with distributed ...

preventative controls. Drive adoption of automation-first principles, reducing dependency on human-driven processes. Contribute to AI-driven operational use cases, including event correlation, anomaly detection, noise reduction, operational insights, and automated remediation. Ensure AIOps capabilities are grounded in reliable telemetry, clear control boundaries, and measurable operational … Operational Excellence Define standards for telemetry, monitoring, alerting, and operational visibility across all critical systems. Ensure services are observable, measurable, and support proactive detection of issues. Improve operational readiness, incident response effectiveness, and time-to-recovery through engineering solutions. CI/CD & Platform Integration Contribute to the design ...

management, BI, CDP/CRM, ad platforms, experimentation, consent/privacy, data warehouses) including build vs buy vs partner recommendations. Build proactive insight systems: anomaly detection, opportunity surfacing, segmentation, attribution-informed signals, and next best actions that guide teams to outcomes. Ensure Analytics actively powers other pillars ...

frameworks, and adaptive access controls. Collaborate with the Senior Architect Information Security and lead the implementation of identity governance automation, leveraging machine learning for anomaly detection and remediation. Ensure seamless integration of multi-factor authentication (MFA) with biometric and mobile device capabilities to improve both security … user experience. Champion the adoption of identity threat detection and response (ITDR) solutions to proactively identify and mitigate identity-based attacks. Develop and maintain the firm's IAM architecture, including identity lifecycle, access governance, and privileged access controls. Design secure authentication and authorization patterns (OpenID Connect, SAML, OAuth ...

identify trends, patterns, and anomalies associated with potential ATO and Send Scam threats. Design and implement experiments to evaluate the effectiveness of fraud detection systems and continuously improve their performance. Collaborate with security analysts and engineers to translate business and security requirements into actionable data insights and solutions. … programming languages such as Python, R, or similar. Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL). Familiarity with anomaly detection, supervised, unsupervised learning methods, deep learning, and graph based solutions Demonstrated ability to work collaboratively in cross-functional teams and effectively ...

develop AI and machine learning solutions Build, validate, and deploy production-ready models Perform exploratory data analysis and feature engineering Develop classification, ranking, and anomaly detection models Support machine learning deployment within containerised environments Troubleshoot and debug code across the development life cycle Work closely with technical … Experience working with time-series data and trend analysis Strong exploratory data analysis skills Additional: Experience with SHAP, LIME, model monitoring, or drift detection Knowledge of rank aggregation techniques such as Robust Rank Fusion (RRF) Experience within regulatory, risk, financial crime, or compliance environments Experience with record linkage ...

develop AI and machine learning solutions Build, validate, and deploy production-ready models Perform exploratory data analysis and feature engineering Develop classification, ranking, and anomaly detection models Support machine learning deployment within containerised environments Troubleshoot and debug code across the development life cycle Work closely with technical … Experience working with time-series data and trend analysis Strong exploratory data analysis skills Additional: Experience with SHAP, LIME, model monitoring, or drift detection Knowledge of rank aggregation techniques such as Robust Rank Fusion (RRF) Experience within regulatory, risk, financial crime, or compliance environments Experience with record linkage ...

delivery in enterprise environments. Proven experience building and deploying end-to-end Machine Learning pipelines in production. Strong knowledge of ML (regression, classification, clustering, anomaly detection) and deep learning (PyTorch and/or TensorFlow). Hands-on experience with Generative AI, including LLMs, RAG systems, and agent ...

Excellent programming skills, predominantly across the Python/Anaconda suite (Scikit-learn, Pandas, Numpy) Understanding financial markets, risk (for example, Know Your Client (KYC), anomaly detection/Machine Learning, project management Excellent interpersonal skills with the ability to collaborate and partner with various teams ...

data Deep Learning NLP + LLMs, GenAI agent pipelines Simulations Graph-based models Time-series forecasting Geospatial modeling Causal inference Reinforcement learning Optimization problems Anomaly detection* **Deployment Experience*** Proven track record of deploying or partnering on **customer-facing production ML systems**.* Proficiency in Python ...

chain, routing, and capacity planning. Leveraging AI methods to inform optimisation heuristics, demand forecasts, and dynamic decision‐support Machine Learning, Data Science & Applied AI Anomaly detection using statistical, ML, and hybrid methods for fault and quality monitoring. RUL estimation and predictive maintenance via survival, failure time ...

including data extraction, transformation, normalisation and quality controls to support scalable AI‐enabled process discovery. Direct the application of ML techniques (clustering, sequence modelling, anomaly detection) to identify automation candidates, bottlenecks, and root‐cause patterns. Shape intelligent automation pathways, working with engineering teams to embed ML‐supported … decision logic into workflow engines, RPA bots, agentic AI and orchestration platforms. Define technical governance and model controls, including monitoring, drift detection, explainability requirements, and compliance frameworks across discovery and automation models. Facilitate workshops and training sessions to build client capabilities in data & AI literacy and process analytics. ...

Threat Detection Engineer required for global legal firm. You will be responsible for advancing the maturity of the SIEM platform alongside other strategic security solutions, working closely with internal teams to improve the organisation's overall security posture. This position focuses on onboarding new log sources, optimising data … Engineering Design and implement detection use cases aligned to MITRE ATT&CK and threat intelligence Build and tune correlation rules, anomaly detections, dashboards, and alerting workflows Continuously refine detections to reduce false positives and improve effectiveness SOC & Incident Response Support Partner with SOC analysts ...

Threat Detection Engineer required for global legal firm. You will be responsible for advancing the maturity of the SIEM platform alongside other strategic security solutions, working closely with internal teams to improve the organisation's overall security posture. This position focuses on onboarding new log sources, optimising data … Engineering Design and implement detection use cases aligned to MITRE ATT&CK and threat intelligence Build and tune correlation rules, anomaly detections, dashboards, and alerting workflows Continuously refine detections to reduce false positives and improve effectiveness SOC & Incident Response Support Partner with SOC analysts ...