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oracle

Senior Data Scientist

Oracle
Nashville, USA
Full-time
Senior · 3+ years experience
Onsite
Discovered 2 weeks ago
OracleSQLPython

Full Job Posting

Qualifications

  • Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $100,700 to $209,500 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: Medical, dental, and vision insurance, including expert medical opinion Short term disability and long term disability Life insurance and AD&D Supplemental life insurance (Employee/Spouse/Child) 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: 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. 11 paid holidays 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. Paid parental leave Adoption assistance Employee Stock Purchase Plan Financial planning and group legal Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment.
  • 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.
  • Demonstrated ability to communicate 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.
  • Experience with cloud infrastructure and networking domain
  • Experience with MLOps, building workflows for model retraining, monitoring and deploying
  • Experience working with ambiguous problem and driving it to the finish line

Responsibilities

  • RESPONSIBILITIES What You’ll Do
  • Lead exploratory research and rigorous statistical analysis to translate 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, ensuring 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, evaluate analytical opportunities, and deliver solutions aligned with measurable business outcomes.
  • Establish and champion data-quality standards, including validation, monitoring, lineage, and remediation practices, recognizing that reliable inputs are foundational to trustworthy analytical and ML outputs.
  • Mentor junior data scientists on statistical rigor, modeling best practices, experiment evaluation, code quality, and effective communication of data-driven findings.
  • Lead the development, evaluation, and fine-tuning of LLM-based solutions for infrastructure-build and data-center-materials use cases, including domain adaptation, retrieval/evaluation strategies, and performance measurement.
  • Stay current on advances in statistics, machine learning, and data science; assess and apply emerging methods to improve business processes, product capabilities, and decision quality.
  • Stay up-to-date with the latest developments in machine learning, statistics, and data science, applying new techniques for process/ product improvements.

Minimum Qualifications

  • Preferred Qualifications (Nice To Have)

Preferred Qualifications

  • Preferred Qualifications (Nice To Have)

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