Principal Data Scientist - Supply Chain Operations

We are seeking a Senior Data Scientist to drive data science and advanced analytics initiatives across Supply Chain Operations in support of the Oracle Cloud business. This role is a highly technical individual contributor position responsible for developing machine learning models, optimization algorithms, and decision-support systems that improve planning, inventory management, logistics, manufacturing, and operational efficiency.

The ideal candidate combines deep expertise in data science and supply chain analytics with strong business acumen. They will work cross-functionally with various teams in Supply Chain including Manufacturing, Planning, and Procurement along to transform complex operational data into actionable insights and scalable analytical solutions.

As a senior IC, this individual is expected to provide technical leadership, establish best practices, and mentor other data scientists without direct people management responsibilities.

*Role is on-site in Nashville, TN or Austin, TX.

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: $114,600 to $234,600 per annum. May be eligible for bonus, equity, and compensation deferral.


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 opinion
2. Short term disability and long term disability
3. Life insurance and AD&D
4. Supplemental life insurance (Employee/Spouse/Child)
5. Health care and dependent care Flexible Spending Accounts
6. Pre-tax commuter and parking benefits
7. 401(k) Savings and Investment Plan with company match
8. 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 holidays
10. 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 leave
12. Adoption assistance
13. Employee Stock Purchase Plan
14. Financial planning and group legal
15. 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.

Career Level - IC4

Key Responsibilities

Supply Chain Analytics & Optimization

·Lead development of advanced analytical models that improve end-to-end supply chain performance.

·Design predictive models for demand forecasting, inventory optimization, capacity planning, supplier performance, transportation, and fulfillment.

·Develop optimization algorithms for production scheduling, network design, allocation, replenishment, and logistics planning.

·Build simulation models to evaluate operational scenarios and support strategic decision making.

Machine Learning & AI

·Develop, validate, deploy, and monitor machine learning models in production.

·Apply statistical modeling, forecasting, anomaly detection, reinforcement learning, causal inference, and optimization techniques where appropriate.

·Evaluate emerging AI technologies and large language model applications that improve supply chain decision making.

Data Science Leadership

·Define analytical approaches for complex business problems with ambiguous requirements.

·Establish modeling standards, experimentation methodologies, and validation practices.

·Lead technical design reviews and influence architectural decisions across analytics platforms.

·Serve as the technical expert for advanced analytics initiatives.

Cross-Functional Collaboration

·Partner closely with Supply Chain Planning, Procurement, Manufacturing, Logistics, Operations Excellence, Finance, and Engineering teams.

·Translate business problems into analytical solutions and communicate findings to technical and executive audiences.

·Drive adoption of analytical products by working with stakeholders throughout solution development.

Data Engineering & Productionization

·Collaborate with Data Engineering teams to build reliable analytical datasets and production pipelines.

·Ensure models are production-ready through automation, monitoring, versioning, and MLOps best practices.

Innovation

·Evaluate new methodologies in machine learning, optimization, and operations research.

·Prototype new analytical capabilities that improve operational performance.

·Publish internal best practices and contribute to the organization's technical excellence.

Required Qualifications

·8+ years of experience applying data science to complex business problems.

·Significant experience supporting supply chain, manufacturing, logistics, or operations organizations.

·Strong programming skills in Python, SQL, C++. R.

·Experience deploying production machine learning models.

·Strong understanding of statistical inference, predictive modeling, and machine learning algorithms.

·Experience working with large-scale structured and unstructured datasets.

Preferred Qualifications

·Experience with MLOps frameworks and CI/CD for machine learning.

·Familiarity with streaming data, digital twins, or real-time operational analytics.

·Experience applying generative AI or large language models within enterprise operations.

Technical Skills

Programming

·Python

Machine Learning

·Forecasting

·Classification

·Regression

·Time-series modeling

·Clustering

·Recommendation systems

·Reinforcement learning

·Anomaly detection

·Causal inference

Optimization

·Linear Programming

·Mixed Integer Programming

·Network Optimization

·Simulation

·Heuristics

·Operations Research