Principal Data Scientist

As a part of the Graviq.ai team, you will be at the forefront of delivering innovative artificial intelligence solutions to address complex industry challenges. Your role will involve leading the design and deployment of enterprise-scale AI/ML solutions focusing on demand forecasting, pricing optimization, promotion effectiveness, and assortment intelligence in CPG environments. You will have the opportunity to architect advanced models using machine learning, deep learning, mathematical optimization, and LLM/agentic AI frameworks. Key Responsibilities: - Lead the design and deployment of enterprise-scale AI/ML solutions for demand forecasting, pricing optimization, promotion effectiveness, and assortment intelligence in CPG environments. - Architect advanced models using machine learning, deep learning, mathematical optimization, and LLM/agentic AI frameworks. - Translate complex business problems into scalable, production-grade data science solutions leveraging modern cloud platforms. - Define model architecture, feature strategy, evaluation metrics, and governance standards for enterprise AI products. - Collaborate with product, engineering, and business stakeholders to deliver high-impact analytics solutions at scale. - Provide technical leadership and mentorship across the data science community. - Work with modern stack including Python, PySpark, Azure, Databricks, distributed ML, and MLOps frameworks. Qualifications Required: - Minimum 10 years of deep expertise in machine learning, forecasting, optimization, and GenAI. - Strong experience in building enterprise-scale AI/ML solutions on cloud platforms. - Proficiency in Sales & Demand Forecasting, Machine Learning / Deep Learning, LLMs & Agentic AI, Mathematical Optimization, Python / PySpark, Cloud ML Platforms (Azure / Databricks), MLOps & Model Governance. - Experience in CPG / Retail Analytics Domain. Join Graviq.ai in shaping next-generation AI/ML-driven retail solutions and contribute to empowering businesses with data-driven insights and strategies to make informed decisions. As a part of the Graviq.ai team, you will be at the forefront of delivering innovative artificial intelligence solutions to address complex industry challenges. Your role will involve leading the design and deployment of enterprise-scale AI/ML solutions focusing on demand forecasting, pricing optimization, promotion effectiveness, and assortment intelligence in CPG environments. You will have the opportunity to architect advanced models using machine learning, deep learning, mathematical optimization, and LLM/agentic AI frameworks. Key Responsibilities: - Lead the design and deployment of enterprise-scale AI/ML solutions for demand forecasting, pricing optimization, promotion effectiveness, and assortment intelligence in CPG environments. - Architect advanced models using machine learning, deep learning, mathematical optimization, and LLM/agentic AI frameworks. - Translate complex business problems into scalable, production-grade data science solutions leveraging modern cloud platforms. - Define model architecture, feature strategy, evaluation metrics, and governance standards for enterprise AI products. - Collaborate with product, engineering, and business stakeholders to deliver high-impact analytics solutions at scale. - Provide technical leadership and mentorship across the data science community. - Work with modern stack including Python, PySpark, Azure, Databricks, distributed ML, and MLOps frameworks. Qualifications Required: - Minimum 10 years of deep expertise in machine learning, forecasting, optimization, and GenAI. - Strong experience in building enterprise-scale AI/ML solutions on cloud platforms. - Proficiency in Sales & Demand Forecasting, Machine Learning / Deep Learning, LLMs & Agentic AI, Mathematical Optimization, Python / PySpark, Cloud ML Platforms (Azure / Databricks), MLOps & Model Governance. - Experience in CPG / Retail Analytics Domain. Join Graviq.ai in shaping next-generation AI/ML-driven retail solutions and contribute to empowering businesses with data-driven insights and strategies to make informed decisions.