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Data Scientist - Yield Optimization (Semiconductors)

Micron Semiconductors
Singapore
Salary Estimate
SGD 110.000 – SGD 180.000
Posting Time
6 Mei 2026
Deadline
6 Mei 2027

Job description

At Micron Semiconductors, we are at the forefront of semiconductor manufacturing and data-driven process optimization. We are seeking an experienced Data Scientist to join our Manufacturing Analytics team in Singapore. You will leverage data engineering, machine learning, and advanced analytics to improve wafer yield, identify bottlenecks, and automate processes across yield optimization initiatives. This role combines rigorous data science with practical manufacturing insights to deliver measurable improvements in product quality, throughput, and cost efficiency. You will collaborate with Yield, Process, and Equipment Engineering teams to translate insights into actionable improvements, while ensuring data governance and model stewardship. If you are passionate about turning data into competitive advantage in a fast-paced semiconductor environment, we want to hear from you.

Key responsibilities include building predictive models, developing robust data pipelines, and delivering actionable dashboards that executives and engineers rely on for decision making. You will drive experimentation, monitor model performance, and apply statistical methods to optimize yields and manufacturing processes. This role offers the opportunity to shape data-driven strategies across global manufacturing operations and accelerate digital transformation in the semiconductor sector.

Responsibility

  • Develop and deploy predictive models to optimize semiconductor yields and process performance across fabrication lines.
  • Build robust data pipelines, data quality checks, and data governance processes to enable reliable analytics.
  • Collaborate with Yield, Process, and Equipment Engineering teams to translate data insights into actionable improvements.
  • Design and implement dashboards and visualizations using Power BI, Tableau, or equivalent tools for stakeholders.
  • Experiment with statistical methods (DOE, A/B testing) and ML algorithms (regression, classification, time-series) to drive yield improvements.
  • Lead model validation, monitoring, and governance, ensuring model performance and compliance with manufacturing standards.
  • Communicate findings clearly to cross-functional teams and translate analytics into operational actions.
  • Mentor junior data scientists and contribute to a data-driven culture across the organization.

Qualification

  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Electrical Engineering, or a related field.
  • 3+ years of experience as a Data Scientist, preferably in semiconductor manufacturing, electronics, or industrial automation.
  • Strong proficiency in Python (pandas, scikit-learn, numpy) and SQL; experience with Spark is a plus.
  • Experience with ML/AI modeling, statistical analysis, and experimental design (DOE, A/B testing).
  • Proficiency in data visualization and storytelling with dashboards (Power BI, Tableau, or equivalent).
  • Familiarity with data engineering concepts, data governance, and data quality management.
  • Excellent communication and collaboration skills; ability to work cross-functionally with engineering, manufacturing, and operations teams in a fast-paced environment.
  • Self-motivated, detail-oriented, and able to thrive in a dynamic, multinational setting in Singapore.

Required Skills

Data Science Machine Learning Python SQL Pandas Scikit-learn NumPy Data Visualization DOE A/B Testing Statistical Analysis Data Engineering Tableau Power BI Big Data Spark Manufacturing Analytics

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