Digital Analytics & IIoT Manager

Who We Are:

Challenge Manufacturing’s mission is to manufacture with operational excellence by empowering our employee-owners. As a leading tier 1 supplier of complex metal assemblies for the global automotive industry, we drive innovative solutions for future mobility. We believe the best ideas come from individual unique perspectives. These ideas combined with the teamwork of industry leaders allow us to accomplish any challenge. Our team members take pride in the work we do and embody our core values of safety, ownership, and teamwork every day;

they are the true driving force in our operations.

Challenge is proud to be one of the largest employee‑owned automotive companies in North America. One of the many benefits of joining the Challenge team is the ESOP program. This program allows Challenge to give shares of the Company to all employee‑owners annually. These shares are an additional retirement benefit that will continue to grow during your time ng part of an ESOP means our employee‑owners share in Challenge’s success!

Challenge is #Quality Driven and #People Powered!

We are seeking a strategic, hands‑on Digital Analytics & IIoT Manager to lead the collection, integration, and analysis of plant‑floor data across a high‑volume automotive manufacturing network. This role is responsible for turning MES/SCADA, PLC, and IIoT data into actionable insights that improve production efficiency, uptime, quality, and predictive maintenance.

The ideal candidate has a strong background in industrial analytics, IIoT deployment, and automotive manufacturing operations, and can collaborate across Production, Maintenance, Engineering, OT, and IT teams to deliver scalable, data‑driven solutions that support vehicle launches, high‑volume production schedules, and continuous improvement initiatives.

• Lead the design, deployment, and management of industrial data pipelines for MES/SCADA, PLCs, and IIoT sensors across multiple plants.
• Implement digital twins, real‑time monitoring dashboards, and predictive maintenance models to prevent unplanned downtime and improve asset utilization.
• Develop and maintain KPIs, operational dashboards, and reporting tools to drive improvements in throughput, OEE, cycle times, first‑pass yield, scrap reduction, and energy usage.
• Integrate IIoT devices and industrial sensors with OT systems, MES/SCADA, ERP, and analytics platforms for seamless end‑to‑end visibility.
• Partner with Production, Maintenance, and Quality teams to identify bottlenecks, optimize processes, and implement data‑driven solutions.
• Manage and mentor Data Scientists, BI Developers, and Analytics Engineers, building analytics capabilities across multiple plants.
• Ensure data governance, integrity, and cybersecurity compliance, in alignment with automotive standards (IATF 16949, ISO 9001, ISO/SAE 21434).
• Apply advanced analytics, statistical modeling, and AI/ML techniques for predictive maintenance, quality monitoring, and process optimization.
• Standardize analytics tools, methodologies, and best practices across sites to enable scalable and repeatable operations.
• Support new vehicle program launches and plant expansions with data‑driven readiness assessments and production monitoring strategies.
• Train plant personnel on analytics dashboards, reporting, and interpretation to foster a data‑driven culture.
• Evaluate and adopt emerging IIoT, edge computing, and analytics technologies to improve plant operations and predictive capabilities.
• Collaborate with OT, Automation, and IT infrastructure teams to ensure secure, reliable, and high‑performance data systems.
• Drive continuous improvement initiatives using predictive analytics to optimize production scheduling, maintenance, and quality assurance.

This will be a M‑F position located at our Corporate Office in Walker, MI. Occasionally, this may require you to arrive early, stay late, or work on weekends, outside of our regular hours, to ensure we successfully meet customer needs, deadlines, or urgent requests.

• Bachelor’s degree in Data Science, Industrial Engineering, Computer Science, or related field required
• Master’s…