Challenge Manufacturing-posted 2 months ago
Full-time • Mid Level
Walker, MI
1,001-5,000 employees

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 at Challenge. Being part of an ESOP means our employee-owners share in Challenge’s success! Challenge is #QualityDriven and #PeoplePowered!

  • 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.
  • Bachelor’s degree in Data Science, Industrial Engineering, Computer Science, or related field required.
  • Master’s degree in Data Analytics, Industrial Engineering, or related field preferred.
  • 7+ years industrial analytics, IIoT, or MES/SCADA experience in automotive or high-volume manufacturing.
  • Hands-on experience with MES/SCADA, PLCs, and industrial sensors (multi-vendor, multi-protocol).
  • Proficiency in industrial communication protocols (EtherNet/IP, OPC UA, MQTT, Modbus, PROFINET).
  • Experience with cloud-based industrial analytics platforms (Azure, AWS IoT/Analytics, Snowflake).
  • Applied experience with AI/ML for predictive maintenance, quality improvement, and operational efficiency.
  • Experience implementing digital twins, edge analytics, and advanced visualization tools (Power BI, Tableau, Grafana).
  • Knowledge of industrial cybersecurity standards and secure OT/IT convergence practices.
  • Proven experience leading multi-plant analytics or IIoT teams.
  • Strong problem-solving, analytical, and communication skills; ability to translate complex data into actionable operational insights.
  • Experience supporting vehicle launch programs and high-volume production schedules.
  • Experience with multi-site standardization, cross-plant KPI monitoring, and analytics deployment in automotive manufacturing.
  • Medical, dental, and vision insurance.
  • Health Savings Account with annual employer contributions.
  • Flexible Spending Accounts.
  • Company-paid Short-Term Disability and Basic Life Insurance.
  • Voluntary Life and Long-Term Disability options.
  • Employer 401k Match.
  • ESOP shares.
  • Tuition reimbursement.
  • Referral Bonus Program.
  • Challenge Incentive Program.
  • Paid time off.
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