Semiconductor Data Scientist information
See salary details
$81.9K - $99.9K
4% of jobs
$99.9K - $117.8K
9% of jobs
$133.1K is the 25th percentile. Wages below this are outliers.
$117.8K - $135.8K
11% of jobs
$135.8K - $153.7K
7% of jobs
The median wage is $159.5K / yr.
$153.7K - $171.7K
50% of jobs
$171.7K - $189.6K
2% of jobs
$189.6K - $207.6K
1% of jobs
$207.6K - $225.5K
0% of jobs
$225.5K - $243.5K
13% of jobs
How much do semiconductor data scientist jobs pay per year?
As of Sep 9, 2026, the average yearly pay for semiconductor data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.
A Semiconductor Data Scientist analyzes large datasets generated during the design, manufacturing, and testing of semiconductor devices to extract insights and optimize processes. They use advanced statistical methods, machine learning, and data visualization tools to identify trends, detect anomalies, and improve yield, quality, and efficiency in semiconductor fabrication. Their work helps companies make data-driven decisions, reduce costs, and accelerate product development cycles.
To thrive as a Semiconductor Data Scientist, you need a strong background in data analytics, machine learning, and semiconductor process knowledge, typically supported by a degree in engineering, computer science, or a related field. Proficiency with programming languages like Python or R, data visualization tools, and familiarity with semiconductor manufacturing systems such as MES are essential. Problem-solving, critical thinking, and effective communication skills help you interpret complex data and collaborate across multidisciplinary teams. These skills enable the extraction of actionable insights, optimization of manufacturing processes, and drive innovation in a highly technical industry.
As a Semiconductor Data Scientist, you will frequently work alongside engineering and manufacturing teams to analyze process data, identify patterns, and develop predictive models that improve yield and quality. Collaboration often involves translating complex data insights into actionable recommendations for process optimization and troubleshooting. Effective communication skills are essential, as you'll need to convey technical findings to colleagues with varying levels of data expertise. This interdisciplinary teamwork is key to driving innovation and efficiency in semiconductor fabrication.
What are popular job titles related to Semiconductor Data Scientist jobs?
For Semiconductor Data Scientist jobs, the most frequently searched job titles are:
