Process Analytics Engineer

Essential Duties & Responsibilities

• Build and deploy process manufacturing statistical and predictive models.
• Conduct data exploration to identify areas of opportunity or risk.
• Provide data investigation, and consultation on how data quality, integrity and/or controls can be improved.
• Discover trends, draw conclusions and provide actionable insights.
• Research and analyze plant issues and build anomaly detection solutions to provide predictive insights to end users to ensure process safety and safe plant operations.
• Work along with Seeq, DataPARC and other programs to become a site in-house expert, identify new use cases, and program the use cases.
• Expand the use of real-time data use and multivariate models (so-called Artificial Intelligence) in manufacturing.
• Determine value case for potentially seldom used, or lightly used, data streams and advance the use case for these data sources via proof-of-concept projects in line with DX goals and plans.
• Engage with Business / Production teams to identify, analyze and propose value driven use cases and have the use cases built on the Analytics platform.
• Provide trainings regarding data analytics technologies for technicians, researchers and engineers in general or in specific areas as required.

Standards Lead BI Development

• Lead BI development to provide stable, high quality, and rapid delivery of reports and dashboards that provide business value.
• Work cross-organizationally to ensure data solutions are secure, efficient, and in alignment with DX Enterprise Standards.
• Ensure a professional and smooth integration of the added value of analytics into successful operations.

Consultation

• Work cross-organizationally to drive adoption of analytics tools and improved data integrity.
• Ensure DX solutions have sound data management practices.
• Provide subject matter expertise and consultation on data aspects of new and/or changing DX solutions.
• Transfer knowledge to the stakeholders with respect to improvement results and the way the improvement is achieved.
• Support teamwork, development and use of data and dashboards in support of business decisions.
• Identify, analyze, prioritize and implement improvement opportunities based on their value to the organization.

Capability Maturity Champion

• Automate and continuously improve core data functions such as collection, extraction, transformation, quality validation, and control.
• Collaborate with business stakeholders to ensure sound data and BI capabilities as well as understanding of the importance of quality data.
• Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
• Help form data management and governance processes within the data engineering team.