This role pays less than
99%
of similar roles. Most pay
$152,875–$214,000
— the shaded band above.
At the midpoint, this role pays about
$108k
versus about
$183k
for comparable roles.
Based on 240 similar postings.
Employer
About Samsung Electronics
Samsung Electronics is a South Korean multinational corporation and a global leader in technology, specializing in consumer electronics, semiconductors, and home appliances.
Samsung Electronics currently has
94 open roles
on FindRole.
Listed pay typically runs
$106,000–$174,500
across 58 roles with salary data.
The Experienced Yield Analysis Engineer joins the semiconductor manufacturing team to monitor wafer processes, drive yield enhancement, and investigate process excursions. This role involves developing predictive yield models by correlating inline metrology, defect inspection data, and FDC metrics to forecast trajectories for ramping and mature technology nodes. The engineer performs advanced data mining and statistical analysis to identify root causes of yield limiters while collaborating with cross-functional teams to ensure process stability. Key responsibilities include leading root cause failure analysis through structured methodologies and building automated analytics pipelines. To succeed, the candidate must utilize Python, JMP, and SQL to manage complex datasets. The role addresses critical manufacturing challenges in semiconductor device physics and CMOS fabrication processes, including lithography, etch, thin films, CMP, diffusion, and implant, ensuring high-quality production across wafer sort and final tests.
Develop and validate yield prediction models using metrology, defect inspection, and FDC metrics.
Forecast yield trajectories for ramping and mature technology nodes to identify risks before testing.
Perform data mining and statistical analysis to identify and mitigate yield limiters across all test stages.
Lead root cause investigations by correlating electrical signatures with physical defects through EFA/PFA partnerships.
Apply machine learning, Python, JMP, and SQL to build automated analytics pipelines for yield data.
Manage major yield excursions and define strategic roadmaps and KPIs for production stability.
Communicate yield health, risks, and technical data to executive leadership and global stakeholders.
What we're looking for
Hold a B.E. or M.Sc. in Electrical Engineering, Materials Science, Physics, Applied Physics, or a related field.
Possess an understanding of semiconductor device physics and CMOS fabrication processes including Lithography, Etch, Thin Films, CMP, Diffusion, and Implant.
Understand electrical parametric testing and defect inspection mechanisms.
Apply data science techniques and machine learning using Python, JMP, and SQL to build yield models and automated pipelines.
Demonstrate strong analytical problem-solving skills to resolve complex process excursions.
Possess strong technical writing and presentation skills to communicate data to diverse audiences.
Ability to work in a fast-paced, 24/7 cleanroom manufacturing environment while managing multiple high-priority investigations.
Must be authorized to access information subject to U.S. export control laws.
Python
AI
Machine Learning
LLMs
Data Pipelines
CI/CD
database s
APIs
EDA Tools
Data Modeling
Visualization
Yield Management
Diagnostics
Hardware Debug
Data Engineering
Python
Rust
Shell Scripting
Linux
CI/CD
Data Pipelines
AI
Machine Learning
EDA Workflows
CAD Navigation Systems
Databases
Version Control
Observability
Automation Frameworks
Workflow Orchestration