make necessary adjustments to maintain quality. 4. Data Management and Analysis Maintain accurate records pest management efforts, and other relevant data. Use data to analyze production trends, identify areas efficiency enhancement in seed production processes. Use data analysis to implement best practices and innovative
culture of safety within the organization. Data Analysis: Utilize data analysis and statistical tools to monitor monitor production performance and make data-driven decisions to improve processes. Cross-functional Collaboration: abilities and strong analytical skills. Proficiency in data analysis and statistical tools. Strong verbal and
QA procedures. Develops,co-ordinates and provides data for annual departmental budget. Plans,schedules Supervises and co-ordinates the complilation of data from NCR's and Supplier complaints. Co-odinates Management Quality Improvement metings and prepares data on the status of the Quality Improvement. Liaises
QA procedures. Develops,co-ordinates and provides data for annual departmental budget. Plans,schedules Supervises and co-ordinates the complilation of data from NCR's and Supplier complaints. Co-odinates Management Quality Improvement metings and prepares data on the status of the Quality Improvement. Liaises
analysis participation. Demonstrate data analytics skills and make data-driven decisions. Ability to work
Ensure proper and timely completion of HR related admin documents (leave, sick leave, FRL, IOD, etc.), Complete
and components for production. Analyze production data and metrics to track performance and identify areas Analytical mindset with the ability to interpret data and make data-driven decisions. Effective communication
capacity constraints. Continuously analyze production data and performance metrics to optimize scheduling and problem-solving skills, with the ability to interpret data and make data-driven decisions. Excellent communication
particular with; FDA regulations, GMP standards, data and metric analysis and the development of Training
Lean Manufacturing Principles Proficiency in using Data & KPI's to drive Operational Improvements Clean