Perform chemical manufacturing process plant data analytics to support improvement initiatives and lead change in Manufacturing. Drive a culture of continuous improvement through data-based problem solving, employee engagement and teamwork. Provide process data analytics to improve operations, achieve metrics, and predict outcomes. Utilize statistical and mathematical techniques to solve problems. Train technicians, researchers, and engineers in data analytics. Use statistical, mathematical, and data science techniques to develop production and process directives, resolve problems, and investigate new technologies. Build and deploy process manufacturing statistical and predictive models. Conduct data exploration to identify opportunities or risks. Provide data investigation and consultation on data quality. Discover trends, draw conclusions, and provide actionable insights. Research and analyze plant issues and build anomaly detection solutions for process safety. Analyze actual to standard variances and report differences to management with recommendations. Compile statistical/analytical reports and dashboards. Use Data Science techniques for multivariate analysis, correlation, and problem identification. Drive AI/ML/DL/Generative AI adoption for predictive monitoring, process control, and anomaly detection. Build algorithms to analyze and improve process and operating conditions. Lead Process Data Analytics development for stable, high-quality, and rapid delivery of valuable reports and dashboards. Collaborate cross-functionally to ensure data solutions are secure, efficient, and aligned with DX Enterprise Standards. Drive adoption of standard data science and improved data integrity. Ensure DX solutions have sound data management practices. Provide data expertise for new/changing DX solutions. Transfer knowledge to stakeholders on improvement results. Support teamwork and data use for business decisions. Identify, analyze, prioritize, and implement improvement opportunities. Champion process plant data analytics solutions. Automate and improve core data functions. Collaborate with business stakeholders for data capabilities and understanding. Assess, test, and implement new or upgraded software. Assist with strategic decisions on new systems.

MINIMUM EDUCATION REQUIREMENTS:

Bachelors degree in Chemical Engineering

MINIMUM EXPERIENCE REQUIREMENTS:

Five (5) years of progressive experience in chemical process data analytics and research, including experience in applying data science and statistical methods to solve complex manufacturing problems, experience using programming languages such as VBA, MATLAB, R or similar, experience applying strong knowledge of databased modelling, statistical and machine learning techniques and deep understanding of chemical manufacturing processes and operation/automation; plus two (2) years of plant process experience.

ALTERNATE EDUCATION REQUIREMENTS:

Masters degree in Chemical Engineering

ALTERNATE EXPERIENCE REQUIREMENTS:

Three (3) years of progressive experience in chemical process data analytics and research, including experience in applying data science and statistical methods to solve complex manufacturing problems, experience using programming languages such as VBA, MATLAB, R or similar, experience applying strong knowledge of databased modelling, statistical and machine learning techniques and deep understanding of chemical manufacturing processes and operation/automation; plus two (2) years of plant process experience.

KANEKA AMERICAS HOLDINGS INC

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Process Data Scientist II