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About the role
Role Brief : - AI, Data Science & Intelligent Analytics Leader is responsible for owning the end-to-end delivery of prioritized AI and advanced analytics initiatives and for institutionalizing robust data science engineering practices across the organization. - The role combines strategic planning with hands-on technical leadership to translate business priorities into scalable, production-grade AI solutions with measurable value. Required Criteria : - Hands-on proficiency in Python for model development and strong SQL for data exploration and feature engineering. - Delivering industrial analytics patterns: time-series forecasting, anomaly detection, optimization, and model validation for real-world plant conditions. - Working experience with modern AI/analytics platforms such as Databricks, Azure Machine Learning, or AWS SageMaker - Ability to design and review production-quality code, define ML deployment patterns, and instrument monitoring (data quality checks, model performance, drift signals). - Familiarity with AI-augmented BI concepts Role Brief : - AI, Data Science & Intelligent Analytics Leader is responsible for owning the end-to-end delivery of prioritized AI and advanced analytics initiatives and for institutionalizing robust data science engineering practices across the organization. - The role combines strategic planning with hands-on technical leadership to translate business priorities into scalable, production-grade AI solutions with measurable value. Required Criteria : - Hands-on proficiency in Python for model development and strong SQL for data exploration and feature engineering. - Delivering industrial analytics patterns: time-series forecasting, anomaly detection, optimization, and model validation for real-world plant conditions. - Working experience with modern AI/analytics platforms such as Databricks, Azure Machine Learning, or AWS SageMaker - Ability to design and review production-quality code, define ML deployment patterns, and instrument monitoring (data quality checks, model performance, drift signals). - Familiarity with AI-augmented BI concepts