Advanced 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.

About the Role:

We are looking for an Advanced Data Scientist to build and deploy scalable GenAI/ML solutions across personalization, recommendation systems, customer analytics, forecasting, and marketing optimization use cases within ecommerce and loyalty platforms.

The ideal candidate should possess strong expertise in LLMs, NLP and modern AI architectures, combined with Machine Learning, Deep Learning, and production-grade AI deployment ecosystems. This role requires a blend of strong statistical foundations, business problem-solving capabilities, and hands-on engineering exposure in modern data platforms.

Key Responsibilities:

• Design, Build and deploy production-grade LLM-powered applications including Retrieval-Augmented Generation (RAG) systems, Semantic search & knowledge-based AI assistants, and Conversational AI & intelligent copilots using Generative AI frameworks.
• Fine-tune, prompt-engineer, and optimize LLMs for business use cases and evaluating & monitor LLM performance (hallucination, grounding, latency, cost)
• Design and implement semantic search, embedding creation pipelines, retrieval-based systems, and vector-search driven applications.
• Develop scalable Machine Learning and Deep Learning for personalization, recommendation engines, customer segmentation, and marketing optimization.
• Work on text-based AI/NLP use cases involving customer insights, conversational AI, search optimization, and intelligent recommendation systems.
• Develop experimentation frameworks including A/B testing and model performance evaluation methodologies.
• Collaborate with Product, Engineering, and Business teams to translate business problems into scalable AI-driven solutions.

Required Skills & Qualifications:

• Mandatory exposure to LLMs, Generative AI, NLP/Text-based AI systems, and embedding creation techniques.
• Strong understanding of Prompt engineering and evaluation techniques, LLM limitations (hallucination, bias, grounding), Token optimization, latency, and cost trade-offs
• Strong hands-on expertise in Python, SQL, Machine Learning, and Deep Learning concepts.
• Experience building recommendation systems, personalization engines, and customer analytics solutions.
• Strong understanding of statistical modeling concepts including regression, clustering, ensemble methods, anomaly detection, and experimental design.
• Hands-on experience working with VertexAI, LangChain, LlamaIndex, FAISS, Spark, Databricks, Snowflake, and Azure Databricks ecosystems in production environments.
• Strong business communication, storytelling, stakeholder management, and problem-solving capabilities.