Starbucks is looking to solve staffing needs across US and Canada stores by architecting and refining predictive models using historical, operational, and external data.
Requirements
- Advanced proficiency in coding languages for data preparation and modeling, including SQL for querying large datasets and Python for building pipelines and statistical models
- Deep understanding of machine learning and statistical techniques, such as regression, classification, decision trees, clustering, and causal inference, with practical experience applying them to real-world problems
- Experience building forecasting models for time series or operational planning
- Background 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
Responsibilities
- Lead forecasting efforts for staffing across US and Canada stores – Architect and refine predictive models using historical, operational, and external data to anticipate staffing needs across diverse store formats and regions.
- Drive exploratory analysis and strategic insights – Conduct deep-dive analyses to uncover trends, inefficiencies, and opportunities, translating complex data into actionable recommendations for system and process improvements.
- Design and scale optimization algorithms – Develop and deploy advanced optimization techniques to recommend staffing levels that balance staffing efficiency, cost, and service quality.
- Influence cross-functional strategy and decision-making – Collaborate with engineering, operations, and product teams to integrate data science solutions into production systems and guide long-term staffing strategy.
- Mentor and elevate the team – Provide technical leadership, share best practices, and support the growth of junior data scientists through coaching and peer review.
- Demonstrate intellectual curiosity and thought leadership – Stay ahead of industry trends, explore emerging methodologies, and proactively identify opportunities to innovate within the staffing domain.
- Thrive in a collaborative, impact-driven environment – Join a high-performing team that values curiosity, innovation, and continuous learning, while driving meaningful business outcomes.
Other
- Masters with concentration in quantitative discipline – Operations , Stats, Math, Comp Sci, Engineering, or similar discipline. Minimum of 2 years of experience
- Strong communication and collaboration skills, with the ability to influence technical and non-technical audiences
- Demonstrated curiosity, analytical rigor, and strategic thinking in solving complex business problems
- Demonstrated curiosity and analytical rigor, with a strong ability to explore complex datasets, identify patterns, and generate actionable insights
- Excellent attention to detail, along with strong written and verbal communication skills to collaborate across cross-functional teams and present findings to stakeholders
