lead data scientist, Pricing Analytics (Seattle, WA)

Starbucks Coffee Company•Seattle, WA

7d•$151,200 - $246,600•Hybrid

About The Position

As a Lead Data Scientist on Starbucks’ Pricing Data Science team, you will lead the development of advanced pricing models and optimization algorithms that shape pricing decisions across company-owned stores in the United States and Canada. You will evolve the pricing system through rigorous analytics, collaboration with cross-functional teams, and influence on strategic workforce planning. The work will affect pricing and customer experience at scale. You will design a scalable, data-driven pricing framework to optimize revenue, incorporating predictive modeling and ad hoc analyses. You will drive pricing and revenue-management data science, identify pricing and promotion opportunities through advanced analytics, and implement optimization strategies using machine learning, simulation, and scenario planning. You will partner with strategy and finance to align pricing tools with business goals. You will also guide data scientists and senior data scientists in advanced analytics, optimization techniques, and business-impact storytelling, while fostering innovation and continuous improvement within the analytics team.

Requirements

5+ years of progressive experience in data science.
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 such as Databricks and Azure.
Experience developing production-grade data pipelines and model outputs.
Excellent communication and data storytelling skills, including the ability to translate complex methods into actionable insights through visualizations and dashboards using tools such as Tableau.
Experience building in-house production systems in complex, data-rich domains.
Mentoring experience.

Nice To Haves

Expertise in Bayesian elasticity models and causal inference.
Experience with 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.

Responsibilities

Design and architect 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 opportunities through advanced analytics.
Implement optimization strategies using machine learning, simulation, and scenario planning.
Partner with strategy and finance to align pricing tools with business goals.
Mentor data scientists and senior data scientists in advanced analytics, optimization techniques, and business-impact storytelling.
Foster innovation and continuous improvement within the analytics team.

Benefits

Medical, dental, and vision insurance.
Basic and supplemental life insurance and other voluntary insurance benefits.
Short-term and long-term disability.
Paid parental leave and family expansion reimbursement.
Paid vacation from date of hire.
Sick time accrued at one hour for every 25 hours worked.
Eight paid holidays and two personal days per year.
Eligible participation in a 401(k) retirement plan with employer match.
Discounted company stock program (S.I.P.) and Starbucks equity program (Bean Stock).
Incentivized emergency savings and financial well-being tools.
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.
Backup care and DACA reimbursement.