Based in Seattle, WA (Hybrid), Starbucks Coffee Company seeks a Lead Data Scientist for Pricing, Data & Analytics to lead the development of advanced pricing models and optimization algorithms 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 the customer experience at scale. Responsibilities include: 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 the 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. Mentoring and talent development: 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. Qualifications include: 5+ years of progressive experience in data science with end-to-end data product and model deployment delivering measurable business impact; strong foundation in machine learning and statistics (regression, classification, clustering, causal inference); proficiency in Python, SQL, and cloud analytics platforms (Databri

Based in Seattle, WA (Hybrid), Starbucks Coffee Company seeks a Lead Data Scientist for Pricing, Data & Analytics to lead the development of advanced pricing models and optimization algorithms 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 the customer experience at scale. Responsibilities include: 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 the 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. Mentoring and talent development: 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. Qualifications include: 5+ years of progressive experience in data science with end-to-end data product and model deployment delivering measurable business impact; strong foundation in machine learning and statistics (regression, classification, clustering, causal inference); proficiency in Python, SQL, and cloud analytics platforms (Databri