Celestica is seeking a Product Data Analyst to analyze the performance lifecycle of complex electronic products, using statistical methods on manufacturing, quality assurance, and post-market reliability data to optimize product yield, minimize defects, and improve overall product quality and cost-effectiveness.
Requirements
- Expert-level proficiency in SQL for extracting and joining data from complex operational databases.
- Proven experience with data visualization tools (e.g., Tableau, Power BI, Looker) to present manufacturing KPIs.
- Experience working with MES (Manufacturing Execution System), ERP, or QMS data structures is highly desirable.
- Strong foundational knowledge of statistics and statistical process control (SPC).
- Demonstrated ability to conduct diagnostic and predictive analytics related to production processes and equipment performance.
Responsibilities
- Develop and maintain analytical models to track First Pass Yield (FPY), defect rates, and process capability metrics.
- Conduct Root Cause Analysis (RCA) using diagnostic analytics to pinpoint process or component failures in complex assemblies.
- Design and build real-time dashboards (e.g., OEE, Downtime) to monitor the performance of key production equipment and manufacturing execution systems (MES).
- Analyze manufacturing cycle times and resource utilization data to identify and eliminate bottlenecks and waste.
- Analyze post-launch data, including field failures, warranty claims, and repair/return data, to provide critical feedback to the New Product Introduction (NPI) and Design teams.
- Write efficient SQL queries to extract and integrate data from various manufacturing systems (MES, ERP, QMS).
- Produce standardized and ad-hoc reports to inform executive decision-making on cost reduction, quality improvement, and capacity planning.
Other
- 2-4 years of experience
- Detail-oriented problem-solver with a passion for continuous process improvement
- ability to clearly communicate technical findings to production managers and engineers.
- This role is split between analytical work at a desk and necessary time on the manufacturing floor to validate data integrity, observe processes, and conduct gemba walks with operational teams.
- Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data.
