1 to 25 of 165 Anomaly Detection Jobs in the UK

effectively with stakeholders across data, governance, and infrastructure. Experience in defining quality strategies , driving process improvements, and implementing automation in large-scale data platforms. Knowledge of data observability and anomaly detection tools (preferred). Industry experience in financial services, insurance, or regulated environments (not essential, but preferred). This role is an excellent opportunity for a Lead More ❯

and maintain scalable, modular pipelines using AWS services (Glue, Lambda, Step Functions, S3), supporting ingestion, transformation, and storage across key business domains. Data Quality & Governance: Implement automated data validation, anomaly detection, lineage, and auditability; enforce consistent naming, access controls, and compliance with GDPR and healthcare standards. Performance & Cost Optimisation: Tune pipelines and query layers (Glue, Athena) for More ❯

and maintain scalable, modular pipelines using AWS services (Glue, Lambda, Step Functions, S3), supporting ingestion, transformation, and storage across key business domains. Data Quality & Governance: Implement automated data validation, anomaly detection, lineage, and auditability; enforce consistent naming, access controls, and compliance with GDPR and healthcare standards. Performance & Cost Optimisation: Tune pipelines and query layers (Glue, Athena) for More ❯

maintain, performance tune, and respond 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 our software release and change More ❯

and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and security measures in line with best practices and regulatory standards. Develop observability and anomaly detection tools to support Tier 1 systems. Work with engineers and business teams to gather requirements and translate them into technical solutions. Maintain documentation, follow coding standards … technical and non-technical teams. Additional Strengths Experience with orchestration tools like Apache Airflow. Knowledge of real-time data processing and event-driven architectures. Familiarity with observability tools and anomaly detection for production systems. Exposure to data visualization platforms such as Tableau or Looker. Relevant cloud or data engineering certifications. What we offer: A collaborative and transparent … Apache Airflow (or similar) and integrating them into containerised CI/CD pipelines (Docker, GitHub Actions, Jenkins, etc.)? Select Which option best describes your experience building observability and automated anomaly detection tooling for data pipelines? Select What best describes your current location and working rights status? Select By submitting your application, you confirm that you have read More ❯

clean, reliable, query-ready datasets used by commercial, operational, and marketing teams. Defining and evolving the data architecture to support scale, cost-efficiency, and data quality. Building validation layers, anomaly detection, and alerting to ensure trustworthy, production-grade pipelines . Working with infrastructure-as-code tools (e.g. CDK, Terraform) to manage data infrastructure securely and repeatably. Driving More ❯

scalable, agnostic testing frameworks for use across agile delivery teams. Promote best practices including Test-Driven Development (TDD) , Behaviour-Driven Development (BDD) , and AI/ML-based testing for anomaly detection and performance validation. Mentor and upskill test and engineering teams in modern, automation-first testing approaches. Collaborate across teams to ensure quality and consistency throughout the More ❯

models using relevant datasets to 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 training Code Review and Documentation More ❯

models using relevant datasets to 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 training Code Review and Documentation More ❯

annotations. Experience in using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products. Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection. Past project experience using the Agile/Scrum project management methodology. Does this sound like you? Apply if you think we're a good match. We'll get More ❯

industry certifications (e.g. DAMA CDMP, DCAM, etc.) Keen interest and familiarity with generative AI frameworks. Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection. Past project experience using the Agile/Scrum project management methodology. Does this sound like you? Apply if you think we're a good match. We'll get More ❯

Route Optimization: Use data analytics to identify the most efficient routes. Optimized routing not only shortens travel time but also makes ETA predictions more reliable. 5. Machine Learning for Anomaly Detection: Implement machine learning algorithms to detect anomalies that could affect delivery times, such as unexpected traffic jams or vehicle breakdowns, and adjust ETAs accordingly. 6. Sensor More ❯

of different data sources into our Lakehouse (Databricks on Azure Data Lake) and its architecture. Be responsible for the reliability and quality of data in the Data Lake (including anomaly detection, data quality checks, reconciliations, access, permission, and retention management, PII treatment, and back-up/restoration plans). Set up and manage platform technologies to support More ❯

s Pricing & Promotions Science, Data, and Insights organization is seeking a highly analytical Business Intelligence Engineer. In this role, you will develop, build, and deliver automated analytics, insights, and anomaly detection tools and technologies, which will deliver the best prices and experiences to our customers. Data, insights, and analytics are at the core of Amazon's culture … Promotions Science organization leverages planet scale multi-modal data on billions of Amazons and external competitor products to build advanced machine learning models for product similarity, substitutability, error detection & correction, and probabilistic price estimation, discovery and discount optimization, promotion & deal recommendation and ranking, and causal short- & long-term impact measurement. We preserve long term customer trust by ensuring More ❯

technical and non-technical teams. Bonus Points For: Experience with orchestration tools like Apache Airflow. Familiarity with real-time data processing and event-driven systems. Knowledge of observability and anomaly detection in production environments. Exposure to visualization tools like Tableau or Looker. Relevant cloud or data engineering certifications. What’s Offered: Competitive salary with two annual discretionary More ❯

technical and non-technical teams. Bonus Points For: Experience with orchestration tools like Apache Airflow. Familiarity with real-time data processing and event-driven systems. Knowledge of observability and anomaly detection in production environments. Exposure to visualization tools like Tableau or Looker. Relevant cloud or data engineering certifications. What’s Offered: Competitive salary with two annual discretionary More ❯

for problem-solving. Preferred Skills: Interest and familiarity with generative AI frameworks. Knowledge of data governance and management, supported by industry certifications (e.g., DAMA CDMP, DCAM). Experience with anomaly detection methodologies. Experience with Agile/Scrum project management methodologies. If this sounds like you, apply to join our team. We will contact you with the next More ❯

core ledger systems, transaction processors, credit bureaus, open banking APIs, and third-party providers. Implement and maintain robust processes to ensure data accuracy, completeness, and reliability. Implement automated checks, anomaly detection, and data validation routines. Deliver production-ready datasets that power credit decision engines, risk models, and affordability assessments in real time. Work closely with credit risk More ❯

core ledger systems, transaction processors, credit bureaus, open banking APIs, and third-party providers. Implement and maintain robust processes to ensure data accuracy, completeness, and reliability. Implement automated checks, anomaly detection, and data validation routines. Deliver production-ready datasets that power credit decision engines, risk models, and affordability assessments in real time. Work closely with credit risk More ❯

retrieval systems or search engine development. Experience with OSINT or intelligence analysis tools and methodologies. Understanding of data privacy regulations and security considerations. Experience with time series analysis and anomaly detection. Familiarity with A/B testing and experimentation design. Experience working with PAI sources and analytical techniques. Knowledge of graph databases and network analysis for relationship mapping. Open More ❯

/Java/Scala/etc.) Experience working with imbalanced datasets and applying appropriate techniques Experience with time series data, including preprocessing, feature engineering, and forecasting Experience with outlier detection and anomaly detection Experience working with various data types: text, image, and video data Familiarity with AI/ML cloud implementations (AWS, Azure, GCP, NVidia More ❯

the Staff Machine Learning Engineer role at Happening As a Staff Machine Learning Engineer in our Fraud Prevention team, you will leverage your expertise to build robust fraud detection models that safeguard our platform in the fast-paced world of online gaming and sports betting. Through innovative data analysis and cutting-edge tools, you’ll play a key … users. What you’ll you be doing: Fraud Detection Modeling developing and optimizing traditional ML algorithms such as gradient boosted trees in fraud detection or anomaly detection domains creating graph analyses and graph connection modelling creating usable datasets for explorative analysis and turn clues into leads and insights for ML modelling Data Engineering … learn) and SQL, with solid experience in relational databases Good knowledge and experience of the broader data science domains, especially large language models or computer vision models used for anomaly detection A track record in deploying machine learning pipelines using tools such as Airflow, SageMaker Pipelines or similar A talent for clean coding, simple solutions, automated testing More ❯

and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and security measures in line with best practices and regulatory standards. Develop observability and anomaly detection tools to support Tier 1 systems. Collaboration & Continuous Improvement Work with engineers and business teams to gather requirements and translate them into technical solutions. Maintain documentation … technical and non-technical teams. Additional Strengths Experience with orchestration tools like Apache Airflow. Knowledge of real-time data processing and event-driven architectures. Familiarity with observability tools and anomaly detection for production systems. Exposure to data visualization platforms such as Tableau or Looker. Relevant cloud or data engineering certifications. What we offer: A collaborative and transparent More ❯

design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas such as … on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and … AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency in Python and More ❯

design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas such as … on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and … AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency in Python and More ❯