STAFF DATA SCIENTIST, Singapore

Our vision is to transform how the world uses information to enrich life for all.

• Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data, identify top yield detractors, and drive continuous improvement.

• Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operations.

• Advanced Analytics & Modeling: Apply data science techniques, statistical modeling, and machine learning to solve yield issues and support defect reduction strategies.

• Experimentation Support: Assist process and integration engineers in running and analyzing Design of Experiments (DOE) to enhance process capabilities and margins.

• Visualization & Communication: Develop automated reports and dashboards using visualization tools such as Dash, Plotly, and Angular to communicate technical concepts and project outcomes effectively to engineering stakeholders.

• Bachelor's degree in Computer Science, Data Science, Statistics, AI, or a related engineering field.
• Minimum 5 years of hands‑on experience in data science, analytics, or scripting applications.
• Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers to resolve production issues.

• Strong Python programming skills and experience with SQL for data extraction and manipulation.
• Familiarity with statistical tools and methodologies such as SPC, DOE, or FDC/EDA, and data‑driven problem solving.
• At least 3 years of experience applying data visualization tools including Dash, Plotly, and Angular.

• Prior experience or internship in the semiconductor industry, electronics manufacturing, or related fields.
• Basic understanding of semiconductor fabrication processes, equipment, and device physics (e.g., CMOS).
• Familiarity with advanced analytics or computer‑based analysis for manufacturing and yield applications.
• Knowledge of memory architecture such as DRAM or NAND.

• Effective communicator and collaborator, capable of bridging the gap between data science and traditional semiconductor engineering teams.
• Analytical and problem‑solving mentality with a demonstrated commitment to quality and continuous improvement in a fast‑paced environment.
• Proven ability to work independently, manage multiple priorities, and deliver high‑quality results.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact .