Principal Data Scientist

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 officeQualificationsDisclaimer:Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.Range and benefit information provided in this posting are specific to the stated locations onlyUS: Hiring Range in USD from: $96,800 to $223,400 per annum. May be eligible for bonus and equity.Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle’s differing products, industries and lines of business.Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.Oracle US offers a comprehensive benefits package which includes the following:1. Medical, dental, and vision insurance, including expert medical opinion2. Short term disability and long term disability3. Life insurance and AD&D4. Supplemental life insurance (Employee/Spouse/Child)5. Health care and dependent care Flexible Spending Accounts6. Pre-tax commuter and parking benefits7. 401(k) Savings and Investment Plan with company match8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.9. 11 paid holidays10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.11. Paid parental leave12. Adoption assistance13. Employee Stock Purchase Plan14. Financial planning and group legal15. Voluntary benefits including auto, homeowner and pet insuranceThe role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.Career Level - IC4ResponsibilitiesResponsibilities: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.Specific responsibilities for this role include: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 productsBasic 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 skillsPreferred 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: 2025-09-30