Applied Scientist

Key Responsibilities

• Research and develop advanced ML/AI algorithms for detecting, classifying, and prioritizing anomalies in real time across OCI’s global network infrastructure, ensuring rapid, automated incident identification.
• Build and optimize predictive models for short-term (minute-level) network demand forecasting to enable dynamic control-loop actions. Develop long-term demand and capacity models to inform network expansion, planning, and business decisions.
• Apply statistical and machine learning techniques to process high-volume telemetry, correlate symptoms and root causes, and enable the observability platform to triangulate problems down to specific devices, links, or regions. Design methodologies and set scientific thresholds for detection, alerting, and automated signal prioritization (not architecture or coding of the underlying platform).
• Define requirements and scientific advancements for data collection frequency, feature engineering, dimensionality reduction, and quality metrics—guiding engineering teams in building world-class observability and analytics.
• Work closely with engineering, network, and product teams, providing scientific guidance on feature design and system integration, and ensuring ML/AI insights are actionable in real-world operations.
• Author high-quality documentation and present findings, best practices, and research outcomes to both technical and non-technical stakeholders. Mentor peers on advanced analytics and networking science.