Leverage large volumes of available data from internal and external sources to lead use case building, conduct research and provide answers to the business. Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modelling. Explore and examine data to find hidden patterns and automate work with the use of predictive and prescriptive analysis. Accountabilities I. Lead use case building and delivery process based on expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation II. Real Time Performance Data and Quality Analyse and interpret data available from machines and operators that can provide KPIs such as OEE and enable data-driven RCA for downtime. Provide predictive model for machine performance and downtime anticipating impacts of changes in yield, scrap and quality. Provide insights in prioritizing issues based on data science, that most impact productivity. III. Fault Prediction and Preventive Maintenance Improve asset management and prevent machine failure through analysis of real time data on temperature, etc. Track available data against optimum performance settings indicated by OEMs to signal preventive maintenance.