Job Description
Join our innovative Security Engineering organization as a Principal Applied Scientist and take the lead in shaping the future of security operations for Oracle's SaaS ecosystem. This is an exceptional opportunity to make a significant impact on the security landscape across a vast enterprise cloud environment.
In this pivotal role, you will architect and develop cutting-edge machine learning and behavioral models that create adaptive, intelligence-driven security capabilities. You will engage directly with large-scale, complex telemetry data, craft models that perform at unprecedented scale, and pioneer transformative techniques for analyzing attacker behavior.
Your Responsibilities:
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Innovate new methods to detect and counteract threats.
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Establish machine learning frameworks for an AI-powered Security Operations Center (SOC).
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Shape the architecture of detection pipelines to influence future security standards.
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Operationalize research findings at petabyte scale.
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Elevate scientific standards within the security organization.
Collaborate closely with Detection Engineering, Red Team, Threat Intelligence, and Data Engineering to identify crucial signals, minimize noise, validate hypotheses, and translate research insights into systems that effectively mitigate risks.
Key Responsibilities:
- Research & Modeling: Develop innovative ML models for anomaly detection, identity analytics, time-series/sequence analysis, graph modeling, and pattern mining. Design experimental protocols and evaluation metrics for threat detection challenges.
- Data & System Understanding: Manage high-cardinality datasets (1.2PB/day+) to uncover valuable signals. Implement efficient modeling strategies for data-scarce environments.
- Cross-Functional Collaboration: Work with teams across the organization to define problems, interpret telemetry, and guide the engineering teams in building detection systems.
- Scientific Integrity: Set clear baselines, validation techniques, and document findings comprehensively. Stay updated with the latest research trends and apply relevant advancements.
Required Qualifications:
- Technical Expertise: Profound knowledge of ML techniques applicable to security such as anomaly detection, statistical modeling, graph analysis, and more.
- Hands-On Skills: Proficient in Python and SQL; experience with distributed data systems and rapid prototyping using frameworks like PyTorch or TensorFlow.
- Experience: PhD or Master's degree in Computer Science, Machine Learning, Applied Mathematics, or relevant experience. A minimum of 10 years in industry or research, ideally with a focus on security telemetry and adversarial domains. Proven impact through deployed models or publications.
Compensation & Benefits: Oracle offers a competitive salary range from $120,100 to $251,600 annually, depending on experience. Additional benefits include medical, dental, vision insurance, 401(k) match, and paid time off among others.
We look forward to your application and the possibility of you joining our team in making a difference in the world of security technology.