lead data scientist - Seattle, WA

Starbucks Coffee Company•Seattle, WA

13h•Onsite

About The Position

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. Are you driven to uncover meaningful insights and build data-powered solutions that shape the future of the world’s leading coffeehouse brand? As a Lead Data Scientist on the Digital Data Science team, you will lead the development of advanced AI/ML models powering personalization & recommendations for Starbucks digital surfaces such as the mobile app, web, digital menu boards and digital drive thru screens. You will drive the evolution of existing models and apply rigorous statistical methods to help achieve 1:1 personalization at the customer level, contextual personalization based on external signals and operational personalization that aligns with our ecosystem of stores. Your work will directly impact millions of Starbucks customers and coffee occasions at scale. The D&A organization spans four key pillars: Customer, Retail Operations, Supply Chain, and Enterprise. Each domain is focused on solving unique and complex challenges through data science. Whether personalizing marketing campaigns, optimizing store operations, improving inventory flow, or unlocking enterprise-wide initiatives, our data scientists apply advanced analytics, experimentation, and modeling to elevate the Starbucks experience. This centralized recruiting approach allows us to match candidates with the most relevant opportunities based on their skills and interests, ensuring alignment with business needs and personal growth. Join a team where data meets purpose to shape what’s next for Starbucks.

Requirements

Education: BS+ with a concentration in a quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, Quantitative Social Science or similar discipline. Master’s and/or PhD preferred
Minimum of 8+ 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
Demonstrated track record of delivering AI/ML models into production with measurable business impact, including expertise in evaluation techniques (A/B testing, lift analysis) and model governance
Strong problem-solving skills with the ability to influence leadership teams at different levels
Strong SQL, databases, and ETL / ELT skills required including cleaning and managing data.
Advanced competency and expertise in Python, R, or some combination
Experience working with distributed data processing frameworks such as Spark and Databricks, and languages such as Java, PySpark, or Scala
Strong collaboration instincts – desire & ability to work with partners to achieve the best outcome for the business.
Excellent communication, presentation, and storytelling skills. The role requires effective communication with colleagues, stakeholders, and leaders from diverse backgrounds.
Proven ability to manage multiple, time-sensitive projects and competing priorities simultaneously to drive projects to completion with minimal guidance and high attention to details.

Nice To Haves

Experience building personalization and recommendation systems (e.g., collaborative filtering, content-based, or hybrid approaches) for digital platforms or mobile apps.
Familiarity with ranking algorithms, reinforcement learning, and contextual bandits for optimizing customer experiences.
Hands-on experience with model deployment in production environments, including monitoring, retraining, and performance optimization at scale.
Strong understanding of offline and online evaluation techniques for recommendation systems (e.g., precision/recall, NDCG, A/B testing).
Knowledge of feature engineering for behavioral and transactional data, and experience leveraging real-time data streams for model updates.

Responsibilities

Lead the design and development of scalable data science solutions from the start to the finish by utilizing machine learning, and statistical analysis. Build scalable processes for cleaning, aggregating, and loading data.
Understanding business initiatives, challenges, questions, concerns, or ideas, transforming them into successful data science solutions, and monitor data science metrics and KPIs
Mentor data analysts & data scientists on best practices, processes, frameworks, and KPIs
Contribute to project planning, and assist the team with estimations, timelines, and prioritization. Assists in developing the analytical roadmap, data, and technology strategy.
Own the end-to-end lifecycle of AI/ML solutions, from ideation and prototyping to production deployment, ensuring robust offline evaluation and real-time performance monitoring.

Benefits

medical
dental
vision
basic and supplemental life insurance
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
two personal days per year
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
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
access to other educational opportunities
access to backup care
DACA reimbursement