Senior Data Scientist

Oracle•Nashville, TN

22d

About The Position

Oracle Cloud Infrastructure’s Data Science and Analytics team is seeking a Senior Data Scientist to address complex technical challenges in infrastructure build processes and develop analytical solutions that improve optimization and efficiency. The role involves researching disparate data sources, building large-scale data pipelines, and deploying large language models in OCI’s Infrastructure organization. The successful candidate will lead data-driven initiatives to help ensure OCI infrastructure can support new regions and expansions, and will work across a complex environment involving multiple organizations, departments, and teams. The Senior Data Scientist will conduct statistical analyses, deploy machine-learning and large language model solutions, develop forecasting models, and lead business intelligence initiatives affecting OCI Infrastructure and Networking. This hands-on role calls for someone who can navigate ambiguity, turn abstract ideas into practical solutions, and take ownership of in-flight projects to move them forward.

Requirements

Bachelor’s degree, or equivalent practical experience, in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Economics, or a related quantitative field.
Strong foundation 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.
Ability to communicate analytical findings clearly to 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 ability to develop, evaluate, and iterate on analytical solutions in an ambiguous environment.

Nice To Haves

Experience with cloud infrastructure and networking.
Experience with MLOps, including building workflows for model retraining, monitoring, and deployment.
Experience working with ambiguous problems and driving them to completion.

Responsibilities

Lead exploratory research and rigorous statistical analysis to translate complex data into 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 for 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 with measurable business outcomes.
Establish and champion data-quality standards, including validation, monitoring, lineage, and remediation practices.
Mentor junior data scientists in statistical rigor, modeling practices, experiment evaluation, code quality, and communicating findings.
Lead development, evaluation, and fine-tuning of LLM-based solutions for infrastructure-build and data-center-materials use cases, including domain adaptation, retrieval and evaluation strategies, and performance measurement.
Keep current with advances in statistics, machine learning, and data science, and apply emerging methods to improve business processes, product capabilities, and decision quality.

Benefits

Medical, dental, and vision insurance, including expert medical opinion.
Short-term and long-term disability insurance.
Life insurance and AD&D.
Supplemental life insurance for employees, spouses, and children.
Health care and dependent care Flexible Spending Accounts.
Pre-tax commuter and parking benefits.
401(k) Savings and Investment Plan with company match.
Paid time off, including flexible or accrued vacation depending on position eligibility.
11 paid holidays.
Paid sick leave.
Paid parental leave.
Adoption assistance.
Employee Stock Purchase Plan.
Financial planning and group legal benefits.
Voluntary auto, homeowner, and pet insurance.