1 to 25 of 43 Anomaly Detection Jobs in England

develop an AI-driven observability and automation platform, leveraging: Telemetry ingestion (Kafka, OpenTelemetry, Fluentd). Streaming analytics (Flink, Spark, CEP engines). AI-driven anomaly detection & automation (AutoGPT, LangChain, MLflow, TensorFlow). Define technical requirements and architecture priorities for engineering teams. Partner with data scientists to improve … AI-driven predictive analytics, anomaly detection, and root cause analysis. Collaborate with banks, trading firms, and financial services IT teams to understand operational challenges. Develop use cases for AI-driven observability, fraud detection, self-healing infrastructure, and compliance monitoring. Work closely with sales and customer More ❯

the team on projects and your day job typically consists of: Help build and improve the algorithms in a scalable manner for AI-based anomaly detection and predictive modelling. Apply and sometimes (co-)invent and implement AI/ML algorithms for processing various types of data (timeseries … sources over various connector pipelines (SQL, Elasticsearch, Kafka, REST APIs, etc.). Tune algorithms and data pipelines for optimal performance. Train, tune, and deploy anomaly detection and predictive models on industrial or IoT data. Knack/experience in consultancy services. Qualifications: Previous hands-on experience in Data More ❯

ll be at the intersection of cutting-edge AI/ML technologies and real-time data processing. You'll work on developing and optimizing anomaly detection algorithms that power our highly scalable stream processing platform. What You'll Do You'll collaborate with a team of skilled … engineers to design, implement, and maintain large-scale AI/ML pipelines for real-time anomaly detection. You will be responsible for training and tuning the models and performing model evaluations using Deep Learning Machine Learning (AI/ML) Models, and Large Language Models, to detect anomalies across billions … of events. You'll design and implement sophisticated anomaly detection algorithms, such as Isolation Forests, LSTM-based models, and Variational Autoencoders, tailored to our unique data streams. Creating robust evaluation frameworks and metrics to assess the performance of these algorithms will be crucial. You'll also work More ❯

stewardship best practices, ensuring they effectively leverage governed data assets and self-service capabilities. Monitoring & Data Quality Assurance: Implement data validation, lineage tracking, and anomaly detection mechanisms to ensure high data quality across PNE analytics initiatives. What can you expect from Mars? Work with diverse and talented More ❯

stewardship best practices, ensuring they effectively leverage governed data assets and self-service capabilities. Monitoring & Data Quality Assurance: Implement data validation, lineage tracking, and anomaly detection mechanisms to ensure high data quality across PNE analytics initiatives. What can you expect from Mars? Work with diverse and talented More ❯

stewardship best practices, ensuring they effectively leverage governed data assets and self-service capabilities. Monitoring & Data Quality Assurance: Implement data validation, lineage tracking, and anomaly detection mechanisms to ensure high data quality across PNE analytics initiatives. What can you expect from Mars? Work with diverse and talented More ❯

quality and transformation integrity. Monitoring & Performance Optimization: Monitor data pipelines with tools like Prometheus and Datadog to ensure optimal performance and health. Proactively implement anomaly detection and optimize system performance and resource allocation. Collaborate with cross-functional teams to align DataOps practices with organizational goals. Apply agile More ❯

to incidents on our big data pipeline infrastructure. Build out 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 ❯

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 ❯

research. ETL & Data Engineering – Build ETL workflows that unify data from multiple sources into a structured format. Ensure Data Quality – Implement validation techniques and anomaly detection for data integrity. Collaborate Across Teams – Work closely with quant researchers, AI/ML engineers, and trading professionals. Automate & Optimize – Streamline More ❯

research. ETL & Data Engineering – Build ETL workflows that unify data from multiple sources into a structured format. Ensure Data Quality – Implement validation techniques and anomaly detection for data integrity. Collaborate Across Teams – Work closely with quant researchers, AI/ML engineers, and trading professionals. Automate & Optimize – Streamline 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 ❯

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 ❯

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 ❯

complex financial datasets to extract insights, optimise risk models, and improve trading strategies. 🤖 Machine Learning Development: Design and implement predictive models for fraud detection, credit scoring, and algorithmic trading. 📊 Data Visualisation & Reporting: Build dashboards and reports to communicate insights to both technical and non-technical stakeholders. 🤝 Collaboration: Work … effectively. Desirable Skills Experience with Large Language Models (LLMs), Natural Language Processing (NLP), and generative AI for financial applications. Familiarity with time series forecasting, anomaly detection, or deep learning techniques . Exposure to financial APIs such as Bloomberg, Refinitiv, or Open Banking. Experience with cloud platforms (AWS … Azure) for model deployment. Understanding of big data technologies like Spark or Hadoop. Knowledge of algorithmic trading, credit risk modelling, or payment fraud detection . Benefits 💰 Competitive Salary & Bonus: £35,000 - £45,000 plus performance-based incentives. 🏡 Hybrid Working: Flexible mix of office and remote work. 📈 Career Growth More ❯

complex financial datasets to extract insights, optimise risk models, and improve trading strategies. 🤖 Machine Learning Development: Design and implement predictive models for fraud detection, credit scoring, and algorithmic trading. 📊 Data Visualisation & Reporting: Build dashboards and reports to communicate insights to both technical and non-technical stakeholders. 🤝 Collaboration: Work … effectively. Desirable Skills Experience with Large Language Models (LLMs), Natural Language Processing (NLP), and generative AI for financial applications. Familiarity with time series forecasting, anomaly detection, or deep learning techniques . Exposure to financial APIs such as Bloomberg, Refinitiv, or Open Banking. Experience with cloud platforms (AWS … Azure) for model deployment. Understanding of big data technologies like Spark or Hadoop. Knowledge of algorithmic trading, credit risk modelling, or payment fraud detection . Benefits 💰 Competitive Salary & Bonus: £35,000 - £45,000 plus performance-based incentives. 🏡 Hybrid Working: Flexible mix of office and remote work. 📈 Career Growth More ❯

and KPIs to continuously iterate and improve the product experience. Work closely with data science and analytics teams to integrate advanced visualization methods (e.g., anomaly detection, forecasting visuals). Act as a subject matter expert to translate user needs and scientific data requirements into compelling visual interfaces More ❯

is responsible for designing, building, and testing machine learning models and systems that can solve real-world problems in domains such as spacecraft autonomy, anomaly detection and classification, natural language processing, uncertainty quantification, and multimodal signal detection & characterization. This position will be headquartered at our 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 ❯

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 ❯

analysis, machine learning, and NLP, with a clear understanding of practical applications and limitations. · Experienced in developing and implementing AI solutions, including classification, clustering, anomaly detection, and NLP. · Skilled in complete project delivery, from data preparation to model building, evaluation, and visualization. · Proficient in Python programming and More ❯

analysis, machine learning, and NLP, with a clear understanding of practical applications and limitations. · Experienced in developing and implementing AI solutions, including classification, clustering, anomaly detection, and NLP. · Skilled in complete project delivery, from data preparation to model building, evaluation, and visualization. · Proficient in Python programming and More ❯

year , requiring 3 days per week onsite in London and 2 days remote . Key Responsibilities: Build and implement AI models for classification, clustering, anomaly detection, and NLP. Manage end-to-end model lifecycle from data prep to deployment and monitoring. Write clean, production-level Python and More ❯

year , requiring 3 days per week onsite in London and 2 days remote . Key Responsibilities: Build and implement AI models for classification, clustering, anomaly detection, and NLP. Manage end-to-end model lifecycle from data prep to deployment and monitoring. Write clean, production-level Python and 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 ❯