Lead data scientist- Pricing, Data & Analytics (Seattle, WA)

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…

• Build a scalable, data-driven pricing framework that optimizes revenue.
• Incorporate predictive modeling, and ad hoc analyses into pricing framework.

• 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.

• 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.

• 5+ years of progressive experience in data science, with a proven track record of end-to-end data product and model deployment that delivers measurable business impact.
• Strong foundation in machine learning and statistical techniques, including regression, classification, clustering, and causal inference.
• Advanced proficiency in Python, SQL, and cloud-based analytics platforms (e.g., Databricks, Azure), with experience developing production-grade data pipelines and model outputs.
• Excellent communication and data storytelling skills, with the ability to translate complex methodologies into clear, actionable insights through compelling visualizations and dashboards using tools like Tableau.
• Experience building in-house production systems in complex and data-rich domains.
• Mentoring experience.

• Expertise in building Bayesian elasticity models and causal inference
• Experience in optimization techniques such as linear programming, mixed-integer programming, or heuristic algorithms for decision support
• Background with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments

• As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits.
• Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year.
• Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools.
• Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities.
• You will also have access to backup care and DACA reimbursement.
• Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies.
• This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative.

• If you…