11 of 11 Remote Anomaly Detection Jobs in London

big data pipeline infrastructure. Own building out key components for observability and intelligent monitoring of data pipelines and infrastructure to achieve early and automated anomaly detection and alerting. Present your research and insights to all levels of the company, clearly and concisely. Build solutions to continually improve More ❯

achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining & Analysis Apply data mining techniques such as clustering, classification, regression, and anomaly detection to discover patterns and trends in large datasets. Analyze and preprocess large datasets to extract meaningful insights and features for model More ❯

Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL). Exposure to spatiotemporal data analysis, including time-series anomaly detection and forecasting. Familiarity with ROS (Robot Operating System) for robotics or simulation integration. Publications in top-tier conferences/journals (e.g. More ❯

varying functions and levels in data quality and root cause analysis techniques. Experience using Power BI, Tableau, or similar tools for data visualisation and anomaly detection. Knowledge of P&C insurance, ideally with some experience of working alongside Pricing teams. Ability to integrate AI-driven insights into your work More ❯

AI 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 handly with the most common libraries. Model Hosting and Monitoring: Host and monitor NLP models More ❯

generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases). Experience with recent trends such More ❯

based on knowledge of Acadian's processes and pertinent new research. Explore structured and unstructured datasets with a focus on data preparation, transformation, outlier detection, and feature engineering. Collaborate on the design of ESG constraints for client-driven investment solutions, help build predictive models and design interactive data More ❯

for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection Security Tooling: Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM Qualifications More ❯

experience applying machine learning to time-series or physiological data. Strong foundation in signal processing and time-series modeling (e.g., deep learning, classical ML, anomaly detection). Proficient in Python and ML frameworks such as PyTorch or TensorFlow. Familiarity with FDA regulatory pathways for medical software (e.g. More ❯

open-source innovation. You'll collaborate with cross-functional teams to bring AI-powered capabilities to life from intelligent documentation assistants to code generation, anomaly detection, search improvements, and beyond. Responsibilities Design, develop, and deploy AI/ML models and systems that enhance the Appwrite platform. Identify More ❯

several of the following areas: computer vision (classical and deep learning), multi-view geometry, multi-object tracking, event detection and/or anomaly detection. System experience . You've built, maintained and monitored complex AI/ML models and systems in production at scale. A proven track More ❯