Lead Data Scientist

About Albertsons Companies Inc. :

As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. Our well-known banners across the United States, including Albertsons, Safeway, Vons, Jewel-Osco and others, serve more than 36 million U.S customers each week. We build and shape technology solutions that solve customers problems every day, making things easier for them when they shop with us online or in a store. We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry. Our success is built on a one-team approach, driven by the desire to understand and enhance the customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, efficient, fun and engaging.

About Albertsons Companies India:

At Albertsons Companies India, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. Our workplace in India is a vital extension of the Albertsons Companies Inc. workforce and important to the next phase in the company's technology journey to support millions of customers lives every day. At the Albertsons Companies India, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer. At Albertsons Companies India associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being.

Albertsons Companies is seeking a highly accomplished Lead Data Scientist to lead the development of advanced forecasting, optimization, and AI solutions that drive store level labor planning and scheduling decisions. In this role, you will serve as a senior technical leader and problem solver, owning complex modeling initiatives and shaping solution designs that convert demand signals into optimized workforce plans. You will work across forecasting, optimization, and agentic AI workflows, partnering closely with Data Science, Engineering, and business teams to operationalize scalable, high impact solutions.

This role is suited for a practitioner who combines deep modeling expertise with strong system thinking and the ability to guide others.

Roles & Responsibilities:

• Own and deliver end-to-end modeling solutions for labor demand forecasting, workforce optimization, and schedule generation.
• Develop and refine advanced time-series forecasting models at store, department, and role level.
• Build and maintain optimization and simulation models for labor allocation, shift planning, and compliance aware scheduling.
• Design and contribute key components of agentic AI systems, collaborating with Principals on orchestration logic and decision frameworks.
• Implement LLM powered features (e.g., RAG based explanations, scenario analysis, planner support) to improve trust and usability of AI outputs.
• Partner with Engineering to productionize models on GCP, Azure and Databricks, ensuring scalability, reliability, and performance.
• Lead technical design discussions, code reviews, and model validation efforts for complex initiatives.
• Mentor Junior Data Scientists, helping elevate modeling quality and engineering rigor across the team.
• Collaborate with stakeholders to translate business objectives into robust analytical solutions.
• Define and track success metrics such as forecast accuracy, optimization quality, schedule adherence, and cost-to-serve impact.

Experience Required:

• Advanced degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or related field.
• 9–11 years of experience applying machine learning, deep learning, forecasting, and optimization to large-scale operational problems.
• Strong hands-on expertise in time-series forecasting, optimization techniques, and simulation modeling.
• Practical experience building LLM-based applications, including RAG pipelines and evaluation approaches.
• Experience contributing to multi agent or autonomous decision systems (e.g., LangGraph or similar frameworks).
• Proficiency in Python and SQL, with solid ML engineering and production deployment practices.
• Experience working in cloud environments like GCP, Azure and Databricks with large data volumes.
• Strong communication skills and the ability to influence technical direction across teams.