6 of 6 Anomaly Detection Jobs in Berkshire

Microsoft Entra ID (Azure AD), SailPoint, ForgeRock, Okta. Familiarity with identity lifecycle management, privileged access management (PAM), and access certification processes. Understanding of event-driven data, behavioral analytics, and anomaly detection methods. Domain Knowledge: Basic understanding of digital identity concepts: SSO, MFA, RBAC and ABAC Knowledge of fraud detection techniques and identity risk indicators is More ❯

Microsoft Entra ID (Azure AD), SailPoint, ForgeRock, Okta. Familiarity with identity lifecycle management, privileged access management (PAM), and access certification processes. Understanding of event-driven data, behavioral analytics, and anomaly detection methods. Regards Chaya More ❯

Microsoft Entra ID (Azure AD), SailPoint, ForgeRock, Okta. Familiarity with identity lifecycle management, privileged access management (PAM), and access certification processes. Understanding of event-driven data, behavioral analytics, and anomaly detection methods. #J-18808-Ljbffr More ❯

Microsoft Entra ID (Azure AD), SailPoint, ForgeRock, Okta. Familiarity with identity lifecycle management, privileged access management (PAM), and access certification processes. Understanding of event-driven data, behavioral analytics, and anomaly detection methods. Regards Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information Technology Industries IT Services and IT More ❯

world deployment. Key Skills & Experience Proficiency in Python and PyTorch for model development. Experience working with image-based machine learning models, including optical, UV, and thermal imaging. Understanding of anomaly detection, predictive maintenance, and synthetic data generation. Experience with high-voltage equipment is a plus. How to Apply To learn more, apply now or send your CV More ❯

is designed, developed, tested, and maintained. This unit will explore the integration of AI tools and techniques—such as large language models, code generation systems, automated testing frameworks, and anomaly detection algorithms—throughout the entire SDLC. The goal is to increase development speed, improve code quality, reduce human error, and enable predictive maintenance. Key use cases, to … be prioritized during the project, also based on the industry needs, include AI-assisted coding, intelligent requirement analysis, automated bug detection and resolution, continuous integration optimization, and AI-driven documentation. Each unit will be at the frontier between fundamental AI methodologies and their rapid, scalable deployment in industrial environments. The goal: create high-impact, market-ready solutions while More ❯