7 of 7 Anomaly Detection Jobs in the North West

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 ❯

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 ❯

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 ❯

collaboratively with internal and external teams to identify opportunities for security improvements and review products that can advance our security capabilities, such as tools that support analysis/detection and other emerging technologies. Gather forensic data and physical equipment, to perform in-depth root cause analysis. Support use case tuning through auditing and approval, alongside developing new detection … security technologies, such as IDS, Web content filters, AV, SIEM, Vulnerability Management, Firewalls, and awareness of their purpose in a layered security approach alongside analysing their outputs for security anomaly detection. In-depth understanding of the cyber threat landscape, advanced adversary tactics, and the MITRE Attack Framework. Strong understanding of low-level concepts including operating systems, Active Directory, Windows More ❯

of-the-art NLP models, Transformers, Agentic Approaches for mixed (temporal and text) data analysis and summarization; Experience with pipeline orchestration tools like Airflow, Argo, etc.; Proven Experience with Anomaly Detection and Forecasting with explainability for temporal and mixed data; Intermediate+ English — ability to participate in written discussions with international teams and clients. Join a mission-driven More ❯

Experience of delivering AI and ML- based products into production environments, with an understanding of both model evaluation and productionisation challenges. Expertise in statistics, hypothesis testing, sampling techniques, and anomaly detection, along with experience applying predictive modelling and regression analysis. Excellent communication and stakeholder management skills, with the ability to juggle multiple projects and guide cross- functional More ❯