lead data scientist, Pricing Analytics (Seattle, WA)
Leads Starbucks' Pricing Data Science team in Seattle, building scalable pricing frameworks, predictive models, and optimization algorithms (ML, simulation, scenario planning) for US and Canada company-owned stores, while mentoring data scientists and partnering with strategy and finance.
- Compensation
- Not disclosed
- Location
- US-WA-Seattle-Starbucks Support Center
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Full description
Now Brewing – Lead Data Scientist! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Lead Data Scientist on the Pricing Data Science team, you will lead the development of advanced pricing models and optimization algorithms that shape pricing decisions across US and Canada company-owned stores. You will drive the evolution of the pricing system by applying rigorous analytics, partnering with cross-functional teams, and influencing strategic workforce planning. Your work will directly impact pricing, and customer experience at scale.
As a lead data scientist, you will…
Design and Architect the Future Pricing Ecosystem
- Build a scalable, data-driven pricing framework that optimizes revenue.
- Incorporate predictive modeling, and ad hoc analyses into pricing framework.
Drive Pricing and Revenue management data science
- Identify pricing and promotion potential through advanced analytics.
- Implement optimization strategies leveraging machine learning, simulation, and scenario planning.
- Partner with strategy and finance to align pricing tools with business goals.
Mentor and Develop Talent
- Guide data scientists and senior data scientists in advanced analytics, optimization techniques, and business impact storytelling.
- Foster a culture of innovation and continuous improvement within the analytics team.