• Data Analysis:
  • Assess field application performance data, evaluating how products perform in real-world conditions and identifying areas for enhancement.
  • Collect, analyze, and interpret production yield data to identify trends, patterns, and opportunities for improvement in manufacturing processes.
  • Use statistical tools and techniques (e.g., regression analysis, hypothesis testing) to assess key metrics such as yield rates, defect rates, and process efficiency.
  • Generate regular reports and/or dashboards to communicate production performance and field application insights to the internal team and customers.
• Customer Interface:
  • Collaborate directly with customers to gather feedback on field applications and product performance.
  • Provide data-driven insights and recommendations to customers based on analysis of field performance data.
  • Work with the customer service and sales teams to ensure that customers’ concerns related to product quality and field application are addressed promptly.
  • Present data findings to customers in a clear, understandable format, supporting decision-making with data-driven insights.

• Cross-Functional Collaboration:
  • Partner with production, engineering, quality assurance, and R&D teams to translate data insights into actionable process improvements.
  • Support the development and implementation of strategies to improve yield and reduce waste, defects, and costs.
  • Communicate complex data analysis results to non-technical stakeholders through presentations and reports.

• Continuous Improvement:
  • Monitor and analyze key performance indicators (KPIs) related to production and field applications to drive continuous improvement efforts.
  • Identify bottlenecks and inefficiencies in the production process and recommend corrective actions based on data analysis.
  • Lead or support special projects aimed at improving overall operational efficiency and product performance in the field.

• Education: Bachelor’s degree in Data Science, Statistics, Engineering, Computer Science, or a related field. Advanced degrees (e.g., Master's) are a plus.
• Experience:
  • 5+ years of experience in data analysis, preferably in a manufacturing, production, or field application environment.
  • Experience with production yield analysis, quality assurance, or operational efficiency improvement is highly desirable.
• Technical Skills:
  • Proficiency in data analysis tools such as JMP, SQL, Python.
  • Experience with data visualization tools (e.g., Tableau, Power BI, JMP) to create insightful dashboards and reports.
  • Strong statistical analysis skills (e.g., regression analysis, process control charts, hypothesis testing).
  • Experience working with large datasets and performing complex analyses to uncover insights.
• Soft Skills:
  • Strong communication and interpersonal skills to interface with customers and internal teams.
  • Ability to present complex data in a clear, concise manner to both technical and non-technical audiences.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work both independently and collaboratively in a fast-paced environment.
  • Ability to lead peers in different functions and organizations and influence the decision-making process for critical technical as well as strategic issues.

• Analytical Thinking: Ability to dissect large data sets, identify key patterns, and provide actionable insights.
• Customer Focus: Strong dedication to understanding customer needs and delivering value based on data-driven insights.
• Results-Driven: Proactive in identifying and solving operational issues and continuously seeking improvements in processes.
• Communication: Clear and effective communicator, both in written reports and verbal presentations.
• Team Player: Collaborative, works well with internal teams across different functions and with external customers.