Job Description

Salary: $100,700 - 209,500 per year Requirements:

• Bachelors degree, or equivalent practical experience, in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Economics, or a related quantitative field.
• Strong grounding in probability, statistical inference, experimental design, hypothesis testing, regression, and predictive modeling.
• Experience applying rigorous statistical analysis to large, complex datasets to answer business questions, quantify uncertainty, and communicate actionable insights.
• Proficiency in SQL and Python or R for data extraction, transformation, analysis, visualization, and reproducible modeling workflows.
• Experience with data warehousing and working with structured and semi-structured data at scale.
• Demonstrated ability to explain analytical findings clearly to both technical and non-technical stakeholders.
• Hands-on experience developing, validating, and deploying machine-learning models, including model selection, feature engineering, performance evaluation, and monitoring.
• Experience evaluating and adapting LLM or generative-AI solutions for business use cases, including prompt design, benchmarking, and quality assessment.
• Collaborative problem-solving skills and the ability to develop, evaluate, and iterate on analytical solutions in an ambiguous environment.
• Preferred: experience with cloud infrastructure and networking.
• Preferred: experience with MLOps, including workflows for model retraining, monitoring, and deployment.
• Preferred: experience driving ambiguous problems through to completion.

• Lead exploratory research and rigorous statistical analysis to turn complex data into clear, actionable answers to strategic business questions.
• Apply data transformation, experimental design, predictive modeling, and machine-learning methods as appropriate.
• Design, fine-tune, and optimize scalable algorithms and models with strong reliability, performance, reproducibility, and operational readiness in high-volume production environments.
• Partner with data scientists, engineers, product teams, and business stakeholders to define data requirements, assess analytical opportunities, and deliver solutions aligned to measurable business outcomes.
• Establish and promote data-quality standards, including validation, monitoring, lineage, and remediation practices.
• Mentor junior data scientists on statistical rigor, modeling best practices, experiment evaluation, code quality, and effective communication of findings.
• Lead the development, evaluation, and fine-tuning of LLM-based solutions for infrastructure-build and data-center-materials use cases.
• Stay current on advances in statistics, machine learning, and data science, and apply emerging methods to improve business processes, product capabilities, and decision quality.
• Jump into in-flight projects and help move them forward quickly.

• AI
• Business Intelligence
• Cloud
• Fine-tuning
• Support
• LLM
• Machine Learning
• MLOps
• Oracle
• Python
• SQL
• Rails

More:

We are working with Oracle to connect exceptional professionals to this opportunity on the Oracle Cloud Infrastructure Data Science and Analytics team. We are seeking a Senior Data Scientist to help solve complex Infrastructure Build challenges, build analytical solutions that improve optimization and efficiency, and support OCIs continued growth across new regions and expansions. This role focuses on infrastructure and networking analytics, statistical analysis, forecasting, machine learning, business intelligence, and LLM deployment. We offer a competitive US hiring range of $100,700 to $209,500 per annum, with potential bonus and equity, plus a comprehensive benefits package that includes medical, dental, and vision coverage, disability and life insurance, flexible spending accounts, commuter and parking benefits, 401(k) with company match, paid time off, paid holidays, paid sick leave, parental leave, adoption assistance, employee stock purchase, financial planning, and voluntary benefits. Career level is IC3.

last updated 39 week of 2026

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