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Jobfoundry
GlobalFoundries

Senior Data Scientist

GlobalFoundries
Foundry OperationsSingaporeOnsitePosted 4 weeks ago
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About the role

AI summarised

As a Data Scientist at GlobalFoundries, you will report to the Lead Data Scientist and play a key role in delivering advanced analytics and technical solutions. This role involves supporting best practices across the full lifecycle of data science projects, from development and deployment to scaling and maintenance. You will contribute to developing and deploying machine learning and statistical models to address complex operational challenges within the semiconductor foundry environment.

FoundryOnsite

Key Responsibilities

  • Translate business needs into predictive and prescriptive analytics solutions in collaboration with Lead Data Scientists and business customers.
  • Support the building of data pipelines for productionalized and scalable predictive and prescriptive analytics solutions with the Manufacturing Data Domain group.
  • Conduct exploratory data analysis and create compelling visualizations using complex, high-dimensional datasets under the guidance of the Lead Data Scientist.
  • Assist in identifying suitable machine learning or statistical approaches and training models for optimal performance, including hyperparameter tuning.
  • Contribute to deploying models into production with assistance from Product Engineers.
  • Validate and monitor models to ensure consistent performance and prevent degradation.
  • Communicate the value of analytics to Fab leadership and business partners, increasing awareness of analytics applications.

Requirements

  • Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Data Science) or a related field.
  • A minimum of 4 years of experience in the analytics space with a proven track record of innovation.
  • Proficiency in R, Python, SAS, SPSS, or STATA, with strong data visualization capabilities.
  • Experience building and scaling optimization and cloud-based solutions, including productionizing recommendation engines.
  • Proven experience with key data science techniques such as forecasting, recommendation systems, logistics optimization, churn analysis, and segmentation.
  • Ability to implement business-focused advanced analytics that address industry-specific challenges.
  • Strong communication skills and proven leadership in guiding cross-functional teams.
  • Demonstrated product mindset with experience working in Agile environments.
  • Ability to build trust with stakeholders and work effectively in ambiguous, unstructured problem spaces.