One Thing

Semiconductor Manufacturing

DATASCIENTIST

S$72–96k ~AI est. Singapore FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“DATA SCIENTIST at One Thing. Skills: Data Science, Machine Learning, Data Engineering, Statistical Modeling. Analyze inline/param/probe data to identify top yield detractors. Drive continuous improvement in yield and process optimization”

What You'll Achieve.

Enhance product yield; Improve process variation; Improve process capability; Enhance process capabilities; Enhance process margins

Industry & Context.

Semiconductor Manufacturing
Problems you'll solve

Root cause analysis; Problem-solving mindset

What They're Looking For.

Must Have

Bachelor's degree in Computer Science, Data Science, Statistics, AI, or related Engineering field, Minimum 2 years of hands-on experience in data science, analytics, or scripting applications, Willingness to learn semiconductor manufacturing principles, Python programming skills, Working experience with SQL, Familiarity with statistical tools, Familiarity with statistical methodologies (SPC, DOE, FDC/EDA), Familiarity with data-driven problem solving, At least 2 years of working experience applying data visualization tools

Nice to Have

Prior experience or internship in semiconductor industry, electronics manufacturing, or related fields, Basic understanding of semiconductor fabrication processes, equipment, and device physics, Familiarity with advanced analytics for manufacturing and yield applications, Familiarity with automated analysis for manufacturing and yield applications, Knowledge of memory architecture (DRAM/NAND)

What You'll Do.

Analyze inline/param/probe data to identify top yield detractors

Drive continuous improvement in yield and process optimization

Extract datasets from SQL databases

Cleanse datasets from SQL databases

Analyze datasets from SQL databases

Apply data science techniques to solve yield issues

Apply statistical modeling to solve yield issues

Apply machine learning to solve yield issues

Support defect reduction strategies

Assist engineers in running Design of Experiments (DOE)

Assist engineers in analyzing Design of Experiments (DOE)

Enhance process capabilities and margins

Develop automated reports using visualization tools

Develop dashboards using visualization tools

Communicate technical concepts to engineering stakeholders

Communicate project outcomes to engineering stakeholders

How You'll Work.

Team & Collaboration

Semiconductor manufacturing engineering teams; Multi-functional process areas; Process and integration engineers; Data science teams; Semiconductor engineering teams

Communication Scope

Technical concepts; Project outcomes

Full Job Description

**Our vision is to transform how the world uses information to enrich life for all.** Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. **_Job Summary_** As a Data Scientist at Micron, you will employ techniques drawn from mathematics, statistics, and information technology to uncover patterns in data, drive predictive models, and develop actionable solutions for advanced semiconductor manufacturing. Your primary focus will be to support Process Integration and Process Engineering teams to enhance product yield and improve process variation. You will interact closely with multi-functional process areas to solve manufacturing line problems and conduct root cause analysis. In this position, you will help develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources—such as inline, param, and probe data—translating them into insights that directly improve process capability and device yield. **_Key Responsibilities_** * Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to 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 engine

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