Director Data Science Labor

Position Title: Director / Senior Director Data Science

About the Role:

Albertsons Companies is seeking a visionary Senior Director of Data Science to lead the design and deployment of advanced data science and AI capabilities that forecast demand, predict labor requirements, and intelligently schedule store teams.

This leader will define the data science roadmap that powers store-level labor precision connecting demand signals, staffing needs, and scheduling automation to elevate both customer experience and operational efficiency.

You will shape the future of how Albertsons plans, allocates, and deploys labor leveraging AI agents that augment and automate decision-making across our 2,200+ stores

Roles & Responsibilities:

• Set the strategic vision for end-to-end labor intelligence from demand forecasting to workforce scheduling enabling right-staffed, right-skilled, and right-timed operations.
• Develop and deploy advanced machine learning and optimization models to forecast store-level demand across departments, and roles.
• Design and implement AI scheduling agents that translate forecasts into actionable labor schedules dynamically adjusting for promotions, local events, weather, and in-store traffic.
• Evaluate and refine agentic AI frameworks that simulate, recommend, and optimize staffing decisions in near real time, learning continuously from execution outcomes.
• Partner with Store Operations, HR, Finance, and Technology to operationalize forecasting and scheduling models at enterprise scale.
• Drive the development of intelligent workforce planning systems that proactively balance cost, compliance, and customer service.
• Lead a world-class team of data scientists and ML engineers fostering innovation, technical rigor, and business partnership.
• Translate complex analytical insights into strategic recommendations for senior executives and field leadership.
• Establish measurable impact metrics: forecast accuracy, explainability, labor efficiency, schedule adherence, and associate productivity uplift.

Experience Required:

• Advanced degree in a quantitative discipline (Computer Science, Data Science, Operations Research, Statistics, Applied Math, or related field).
• 10+ years of experience applying advanced analytics, forecasting, and optimization techniques to solve operational problems preferably in retail, logistics, or workforce management.
• Proven track record in demand forecasting, workforce optimization, and scheduling automation at scale.
• 5+ years of leadership experience building and managing high-performing data science teams.
• Deep expertise in in Time-series forecasting, reinforcement learning, optimization, and multi-agent systems.
• Technical proficiency in Python, SQL, and production deployment on Snowflake, Azure Databricks, or similar big data platforms.
• Demonstrated ability to bridge data science with business operations influencing executive stakeholders and field leaders to embed AI-driven decisioning.
• Strong communication and storytelling skills to simplify complex technical concepts into strategic business narratives.

Preferred Skills:

• Experience building AI or agent-based systems for decision automation, particularly in labor scheduling or workforce management.
• Strong grounding in operations research, constraint optimization, and simulation modeling.
• Familiarity with retail store operations, labor laws, and workforce planning systems.
• Experience designing closed-loop learning systems where forecast accuracy and scheduling efficiency continuously improve through feedback.