Manufacturing Yield & Device Analytics Engineer

Job Title

Manufacturing Yield & Device Analytics Engineer

Process Engineering Manager

San Marcos, Texas

We have one goal: to manufacture quality magnets! We are looking for exceptional individuals who want to learn, build, and lay a foundation for our company for the years to come.

You will be responsible for tracking, optimizing, analyzing, and sustaining manufacturing performance to directly improve operational efficiency, product quality, yield performance, and cost-effectiveness. This role completely bridges physical manufacturing fundamentals with advanced analytical problem‑solving, deep process capability analysis, and massive data‑driven decision‑making. The ideal candidate behaves like an analytical sleuth: leveraging manufacturing data trends, statistical analysis, and process validation to drive yield optimization, eliminate waste, and deliver concrete process capability statistics back to design engineering to establish realistic manufacturing design rules.

• Competitive Base
• Medical/Dental/Vision insurance on day 1 of employment
• Health Saving Account (HSA) with Employer contribution
• Employee Assistance Program
• 401(k) retirement plan and match program
• Long Term Disability (Employer Paid)
• Short Term Disability (Employer Paid)
• Paid Time Off (eligible after 90 days of employment)
• Sick Leave (eligible after 90 days of employment)
• Company Paid Holidays

At Noveon Magnetics, we believe our diversity makes us who we are, and we strive every day to build a culture where everyone feels welcome.

• Drive Yield Improvement:
  Utilize data analytics and statistical methodologies to proactively identify process variation, pinpoint production inefficiencies, and execute targeted yield improvement and waste reduction opportunities.
• Statistical Performance Tracking:
  Analyze high‑volume manufacturing data trends, SPC metrics, scrap rates, equipment downtime, cycle times, and overall yield performance to spearhead continuous improvement initiatives.
• Lead Advanced DOE:
  Direct complex Design of Experiments (DOE) activities to establish robust process windows, stabilize process robustness, and achieve challenging process capability targets.
• Predictive Performance Modeling:
  Develop predictive and preventive improvement strategies through analytical modeling and process performance evaluation.

• Define Manufacturing Design Rules:
  Deliver precise process capability numbers and statistical performance metrics to Design Engineering to help define, refine, and enforce realistic design rules for optimal manufacturing scaling.
• Cross‑Functional
  
  Collaboration:
  
  Collaborate cross‑functionally with Production, Quality, Supply Chain, and Operations teams to instill a culture of rigorous, data‑based decision‑making across the organization.
• Root Cause Diagnostics:
  Apply advanced root cause analysis methodologies (including 8D, 5 Whys, Fishbone, Pareto Analysis, and full CAPA implementation) to diagnose sudden process disruptions or quality events.

• Quality & Regulatory Compliance:
  Ensure all yield‑enhancement initiatives and process changes conform to company Quality Management Systems (QMS), supporting ongoing compliance with ISO 9001 and automotive standards.
• Support Digitization & Industry 4.0:
  Support manufacturing digitization, automation, and smart factory initiatives to improve process consistency and unlock deep operational visibility.
• Equipment Capacity Evaluation:
  Evaluate manufacturing equipment performance, capacity limitations, tool utilization, and baseline process efficiency.
• Product Cost Analytics:
  Conduct thorough product cost analyses including labor touch‑time, machine utilization, scrap generation, cycle time, and process‑related cost drivers.

Update and maintain critical Process FMEAs (PFMEAs), Control Plans, and process risk assessments based on ongoing yield data analysis.

• Education:
  
  Bachelor’s degree in Mechanical Engineering, Manufacturing Engineering,…