onsite
Senior Specialist, Yield Management - GTM AA Data Scientist
Data Scientist
Lead data science initiatives for yield management, applying Bayesian modeling and machine learning on AWS and Azure platforms while implementing CI/CD pipelines to drive revenue optimization and strategic decision‑making.
About the role
Key Responsibilities
- Design and implement Bayesian statistical models to forecast demand, pricing, and inventory allocation for GTM AA products.
- Develop, test, and deploy machine‑learning pipelines on AWS and Azure, ensuring reproducibility through CI/CD automation.
- Collaborate with product, finance, and engineering teams to translate business objectives into data‑driven solutions that maximize yield.
- Monitor model performance in production, conduct root‑cause analysis, and iterate to improve accuracy and scalability.
- Document methodologies, create visualizations, and present insights to senior stakeholders to support strategic decisions.
Requirements
- 5+ years of experience in data science or quantitative analytics, with a focus on yield or revenue management.
- Proficiency in Python and statistical libraries (e.g., PyMC, Stan, scikit‑learn) for Bayesian modeling and machine learning.
- Hands‑on experience with cloud platforms (AWS, Azure) and CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions.
- Strong analytical mindset, ability to work with large, complex datasets, and communicate findings clearly.
- Advanced degree (M.S. or Ph.D.) in Statistics, Computer Science, Operations Research, or a related field is preferred.
Skills
pythonmachine learningawsazurecicd