Principal 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 an exceptional Principal Data Scientist to architect, develop, and scale advanced forecasting, optimization, and agentic AI solutions that power store level labor planning and scheduling across 2,200+ locations.

This role is designed for a deeply technical leader who thrives at the intersection of time series forecasting, optimization, and modern AI systems (LLMs, RAG, and multi-agent frameworks). You will be responsible for building intelligent systems that transform demand signals into precise staffing recommendations — dynamically adapting to promotions, seasonality, local events, weather, and real time store activity.

As a Principal Data Scientist, you will serve as a technical authority and mentor, shaping modeling strategy, system design, and execution standards, while partnering closely with cross functional stakeholders to operationalize AI at enterprise scale.

Roles & Responsibilities:

• Architect and develop end to end labor intelligence solutions — from demand forecasting through workforce optimization and schedule generation.
• Design, implement, and productionize advanced time series forecasting models for store, department, and role level demand.
• Build and optimize workforce scheduling models balancing cost, service levels, and compliance constraints.
• Design and deploy agentic AI systems (using LangGraph or similar frameworks) that autonomously reason, plan, and adapt labor decisions in near real time.
• Develop LLM powered components using RAG pipelines for explainability, decision support, and interaction with planners and operators.
• Partner with engineering to build scalable, reliable pipelines on GCP, Azure and Databricks, ensuring high performance model training and low latency inference.
• Evaluate and design closed loop learning systems, where forecast accuracy and scheduling effectiveness continuously improve based on execution feedback.
• Provide technical leadership and mentorship to senior and mid level data scientists — setting best practices for modeling, experimentation, and production rigor.
• Collaborate closely with Store Operations, HR, Finance, and Technology to translate complex models into actionable, trusted decisions.
• Communicate advanced analytical insights clearly to both technical and non technical stakeholders, enabling confidence in AI driven labor decisions.
• Define and monitor model success metrics including forecast accuracy, optimization efficiency, schedule adherence, explainability, and operational impact.

Experience Required:

• Advanced degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.
• 11–13 years of experience applying machine learning, deep learning, forecasting, and optimization to large scale operational problems.
• Deep, hands on expertise in time series forecasting, optimization (linear, mixed integer, and heuristic methods), and simulation.
• Proven experience building LLM based systems, including RAG architectures, prompt orchestration, and evaluation strategies.
• Strong experience with multi agent systems, agent workflows, or decision automation frameworks (e.g., LangGraph or similar).
• Extensive hands on development in Python and SQL, with disciplined software engineering and ML production practices.
• Experience deploying models in cloud native environments, preferably GCP, Azure and Databricks, with large scale data systems.
• Demonstrated ability to influence technical direction and architectural decisions without direct people management responsibility.
• Strong collaboration skills with engineering, product, and business teams to deliver measurable, real world impact.