Principal Data Scientist

OverviewThe 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 officeCareer Level - IC4The position may include other standard corporate notices as applicable. ResponsibilitiesResponsibilities: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 modelingCollaborate with data scientists and other stakeholders to understand data needs and develop solutions that meet those needsCreate comprehensive data strategy to enable reporting and business analyticsConduct research to evaluate data and answer strategic business questionsGenerate actionable insights and enable reporting through data transformation, statistical analyses, or machine learning methodsFine-tune and optimize algorithms and models to ensure scalability, reliability, and performance at a high levelDevelop and maintain data architectures that support data warehousing, data lakes, and data governanceWork with cross-functional teams to integrate data pipelinesEnsure data quality, integrity, and security across all data pipelines and systemsDevelop and maintain metrics and monitoring to ensure data pipeline performance and reliabilityChampion data engineering and data science principlesProvide guidance and mentorship to junior data scientists, contributing to team knowledge and best practicesStay up-to-date with the latest developments in machine learning, statistics, and data science, applying new techniques to improve processes and products Basic QualificationsBS (or equivalent experience) in Data Science, Computer Science, Applied Mathematics, Engineering, or related quantitative or technical field8+ years of data science or software engineering experienceExperience 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 dataStrong understanding of data governance, data quality, and data security principlesExcellent communication and collaboration skills Preferred QualificationsData visualization and polished communication skills.Maturity, judgment, negotiation/influence skills, analytical skills, and leadership skillsSelf-driven problem solver; able to adapt and thrive in a dynamic, ambiguous, and customer-focused environmentHighly analytical, technically proficient, and able to learn new tools and ML models quicklyExperience with GenAI LLM modelsExperience with MLOps, building workflows for model retraining, monitoring and deployingExperience with ML frameworks such as TensorFlow, PyTorchExperience with cloud-based data platforms such as OCI, AWS, GCP, or AzureExperience with data visualization tools such as Oracle Analytics Cloud, Tableau, Power BI #J-18808-Ljbffr

Created: 2025-09-21