Data Scientist 2

Lam Research

Quick summary

Work type
On-site
Location
Fremont, CA
Salary
$86,000–$183,000 / yr
Posted
today
Closes
Dec 28, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $159k
This role $134k
$72k most similar roles pay here $217k

This role pays less than 63% of similar roles. Most pay $126,800–$191,250 — the shaded band above. At the midpoint, this role pays about $134k versus about $159k for comparable roles.

Based on 240 similar postings.

Employer

About Lam Research

Lam Research Corporation is a leading American supplier of wafer-fabrication equipment and services to the global semiconductor industry.

Lam Research currently has 249 open roles on FindRole.

Listed pay typically runs $114,000–$253,000 across 116 roles with salary data.

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View all roles at Lam Research

At a glance

TL;DR · Data Scientist 2

We are seeking a Data Scientist at the junior to mid-level for our Selective Etch Product Group in Fremont, CA. This role involves conducting professional process engineering research and development from concept through equipment evaluation, focusing on predictive modeling and systematic root cause analysis within a collaborative team environment. You will develop advanced test vehicles, compile and evaluate data to set process specifications, and communicate technical results effectively across various audiences. The ideal candidate has experience in applying advanced data science for process engineering, lab experimentation skills, and expertise with AI, machine learning, and sparse data tools. A background in statistical analysis, SPC, DOE, chemistry, and surface science is beneficial, along with strong organizational and collaboration abilities.

What you'll do

  • Develop predictive models from early experimentation to infer physical mechanisms in semiconductor equipment.
  • Design advanced test vehicles for systematic root cause analysis in process engineering.
  • Compile and evaluate test data to set appropriate limits and variables for process specifications.
  • Apply AI and machine learning methodologies to complex semiconductor capital equipment challenges.
  • Utilize statistical analysis tools like SPC and DOE for process optimization and control.
  • Conduct lab experimentation to refine data analysis and modeling techniques.

What we're looking for

  • Experience in applying advanced data science for process engineering and applications development.
  • Expertise in AI and machine learning methodologies with sparse data analysis tools.
  • Strong background in statistical analysis, modeling, SPC, and DOE.
  • Chemistry knowledge and laboratory experience; surface science understanding preferred.
  • Excellent communication skills to explain technical results to varied audiences.
  • Ability to manage multiple tasks, react to shifting priorities, and work effectively in a matrix environment.

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