Job Summary
The Fab Statistician serves as the statistical and data science expert within HP Inkjet MEMS Manufacturing in Singapore, driving yield improvement, process optimization, and data-driven decision making. The role integrates advanced analytics, AI, and statistical methods into manufacturing workflows while partnering closely with engineering, quality, and operations teams to ensure robust and high-yield production.
Responsibilities
- Statistical Consulting, Manufacturing Support & Training
Serve as the statistical expert embedded in MEMS Fab operations to support yield improvement and process optimization. Define sampling strategies, SPC systems, process capability metrics, and DOE. Partner with engineering and operations teams to translate data into actionable insights. Provide training on statistical methods, JMP, and data analytics tools, and support measurement system validation.
While primarily supporting the MEMS Fab, the role is also expected to provide statistical expertise across the broader Inkjet Manufacturing operations in Singapore.
- Quality System & Audit Support
Integrate statistical methods into quality systems and manufacturing standards. Define sampling and monitoring strategies to improve product quality, cost, and reliability. Support internal and external audits as a statistical advisor and contribute to continuous improvement initiatives across the Fab.
- AI, Advanced Analytics & Yield Modelling
Develop and deploy AI and machine learning models for yield prediction, excursion detection, and process optimization. Build automated data pipelines and analytics solutions using Python, R, and SQL. Enable digital manufacturing by integrating advanced analytics into fab systems and driving adoption of data-driven decision making.
Required Skills & Competencies
- Strong foundation in statistical methods including SPC, DOE, sampling plans, process capability analysis, and measurement systems analysis. Proficiency in JMP and programming languages such as Python, R, or SQL. Experience in data analysis within semiconductor, MEMS, or high-volume manufacturing environments is preferred. Strong communication and stakeholder management skills, with the ability to translate complex analytics into practical manufacturing actions.
Education & Experience Recommended
- Four-year or Graduate Degree in Statistics, Data Science, Engineering, or a related discipline. Experience in semiconductor, MEMS, or advanced manufacturing is preferred. Candidates with strong applied analytics or AI experience, particularly in manufacturing environments, are highly valued.
Preferred Certifications
NA
Cross-Org Skills
- Effective Communication
- Results Orientation
- Learning Agility
- Digital Fluency
- Customer Centricity
Impact & Scope
- Impacts multiple teams and may act as a team or project leader providing direction to team activities and facilitates information validation and team decision making process.
Complexity
- Responds to moderately complex issues within established guidelines.
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