Advantest

Data Analyst – Advanced Analytics & AI (m/f/d)

Advantest · Böblingen, Baden-Württemberg, Germany

Semiconductor Manufacturing · 1,001-5,000 employees

7 h ago
Mid (2-5 yrs) Full-time Germany
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About the role

You will analyze complex datasets from manufacturing, engineering, and customer operations to derive actionable insights for product quality and excellence. Additionally, you will integrate AI-driven approaches and automate analytical workflows to improve efficiency across the product lifecycle.

What they look for

Data Analysis Python SQL Statistical Analysis Machine Learning Artificial Intelligence Pandas NumPy SciPy Scikit-Learn Data Visualization Root Cause Analysis Six Sigma Design Of Experiments Statistical Process Control Linux

Requirements

Candidates must hold a Bachelor's or Master's degree in a quantitative discipline and possess strong experience with Python, SQL, and statistical analysis. Proficiency in communicating complex technical findings to diverse audiences and experience with large-scale technical datasets are essential.

Full description

As part of a global cross-functional team, you will transform complex technical data into actionable insights that drive product quality, manufacturing excellence, and customer satisfaction. You will work with large-scale engineering, production, and customer data throughout the entire product lifecycle.

  • Analyze large and highly complex datasets originating from manufacturing, engineering, qualification, field operations, subcontractors, and customer deployments.
  • Perform advanced statistical analyses to identify trends, anomalies, dependencies, and root causes.
  • Conduct correlation studies across multiple data sources and product lifecycle stages to uncover hidden relationships and systemic effects.
  • Design and execute qualification and validation analyses to support engineering decisions and product improvements.
  • Deliver fast-turnaround ad-hoc investigations for critical production, quality, and customer issues.
  • Evaluate and integrate AI-driven approaches into existing analytical workflows.
  • Identify opportunities to automate analytical processes and improve analytical efficiency through advanced methods.
  • Stay current with emerging data science, AI, and analytics technologies and assess their applicability to business challenges.

Qualifications

  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related quantitative discipline.
  • Strong analytical mindset with the ability to solve complex technical problems using data.
  • Experience analyzing large-scale technical, manufacturing, test, measurement, or production datasets.
  • Solid understanding of statistical methods and experimental data analysis.
  • Practical experience with Python and modern data analysis libraries (e.g., Pandas, NumPy, SciPy, Scikit-Learn).
  • Experience working with SQL-based data environments.
  • Excellent English communication skills, both written and spoken.
  • Ability to clearly communicate complex analytical findings to both technical and non-technical audiences.
  • Self-driven, proactive, and comfortable working with ambiguous and rapidly changing analytical challenges.

 

Preferred Qualifications:

  • Experience with AI, machine learning, predictive analytics, or data science methodologies.
  • Experience with semiconductor manufacturing, automated test equipment (ATE), electronics manufacturing, or other high-tech industries.
  • Experience with Tibco Spotfire, Power BI, Tableau, or similar analytics platforms.
  • Experience working directly with customers on technical investigations or problem resolution.
  • Knowledge of quality methodologies such as Six Sigma, Design of Experiments (DoE), Statistical Process Control (SPC), or Root Cause Analysis.
  • Familiarity with Linux-based environments.
  • Experience with SQL optimization and large-scale data architectures.
  • Knowledge of modern data platforms, cloud analytics environments, or NoSQL databases.
  • Experience working in global, cross-cultural organizations.
  • German language skills.