Key Responsibilities: Apply statistical, optimization, and machine learning methods to large, complex data to analyze the data, extract insights, and create models to provide actionable recommendation to solve plant chronic problem, improve operational excellence and accelerate innovationCollaborate with cross-functional teams to implement end-to-end model development process from identifying business problems to executing models in a production environment.Research and develop new advanced technology and modeling techniques to enhance the team’s ability and business outcome Qualifications:Strong in Data Visualization tools, such as Power BI and DAX, Tableau, R-Shiny, Python- Dash.Proficiency in Data Analytics Techniques, such as classification, clustering, anomaly or outlier detection, regression analysis, prediction, etc.Knowledge in existing and emerging Data Analytics tools is preferable  (such as Python, R, Rapid Miner, AutoML, Google Cloud Platform, Amazon Web Service, Microsoft Azure, etc.)AI and Machine Learning experiences in the following area: Time Series Analysis, Anomaly Detection, Process Optimization, Surrogate Model, Hybrid Model, Predictive Analytics or Real-time Data Analytics of Performance and Quality, Preventive Maintenance and Fault Prediction, Product Design and Development, Inventory Management and Demand Forecasting, Computer Vision ApplicationsExcellence communication skill and coordinating skillsGood analytical and problem-solving skillsTeam-working skillsStrong problem solving and project management skillsStrong written, verbal communication, presentation, and Visualization skills.Experience with using query languages such as SQLSelf-driven and creative