Overview The Oracle Cloud Infrastructure Compute team is seeking a passionate, experienced Principal Data Scientist to tackle complex technical challenges of the Compute and AI Infrastructure, building sophisticated analytical and optimization system to drive infrastructure optimization and efficiency improvements through data analysis, AI/ML/DL modeling and data visualization. As OCI continues to scale to the demand of an ever-growing customer base and regions, we need hands-on scientists who can lead data-driven initiatives to ensure OCI continues to provide an outstanding customer experience while continuously improving the efficiency of OCI Compute and AI Infrastructure. The ideal candidate is someone who thrives in the face of ambiguity and can quickly distill abstract ideas into concrete solutions and has a proven track record of delivering business intelligence and reporting solutions across a highly complex environment involving multiple organizations, departments and teams. Location: Seattle, WA - hybrid role 3 days in office Career Level - IC4 The position may include other standard corporate notices as applicable.

Responsibilities Responsibilities: The Principal Data Scientist will be responsible for designing, building and maintaining large-scale data pipelines that support statistical analyses and machine learning model testing, and deployment, forecasting model for infrastructure maintenance and lead business intelligence initiatives that impact both product and business for OCI. In addition, this specific role requires a passion for solving high-impact problems and the ability to jump into any in-flight project and get it on the rails. Design, build, and maintain large-scale data pipelines for statistical analysis and ML modeling Collaborate with data scientists and other stakeholders to understand data needs and develop solutions that meet those needs Create comprehensive data strategy to enable reporting and business analytics Conduct research to evaluate data and answer strategic business questions Generate actionable insights and enable reporting through data transformation, statistical analyses, or machine learning methods Fine-tune and optimize algorithms and models to ensure scalability, reliability, and performance at a high level Develop and maintain data architectures that support data warehousing, data lakes, and data governance Work with cross-functional teams to integrate data pipelines Ensure data quality, integrity, and security across all data pipelines and systems Develop and maintain metrics and monitoring to ensure data pipeline performance and reliability Champion data engineering and data science principles Provide guidance and mentorship to junior data scientists, contributing to team knowledge and best practices Stay up-to-date with the latest developments in machine learning, statistics, and data science, applying new techniques to improve processes and products

Basic Qualifications BS (or equivalent experience) in Data Science, Computer Science, Applied Mathematics, Engineering, or related quantitative or technical field 8+ years of data science or software engineering experience Experience with data warehousing and data lake technologies such as Oracle Object Storage, Apache Hadoop, Apache Hive, or Amazon Redshift. Experience analyzing data, generating insights, and telling stories with data Strong understanding of data governance, data quality, and data security principles Excellent communication and collaboration skills

Preferred Qualifications Data visualization and polished communication skills. Maturity, judgment, negotiation/influence skills, analytical skills, and leadership skills Self-driven problem solver; able to adapt and thrive in a dynamic, ambiguous, and customer-focused environment Highly analytical, technically proficient, and able to learn new tools and ML models quickly Experience with GenAI LLM models Experience with MLOps, building workflows for model retraining, monitoring and deploying Experience with ML frameworks such as TensorFlow, PyTorch Experience with cloud-based data platforms such as OCI, AWS, GCP, or Azure Experience with data visualization tools such as Oracle Analytics Cloud, Tableau, Power BI

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