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Quest Global

Engineering services, digital transformation, asset management

Data Science Engineer

Data ScienceConfirmed live in the last 24 hours
Full-timeChitose, Hokkaido, JapanNo salary listedIn-person

About the Job

Requirements

  • Approximately three years of experience.
  • Experience using analysis software such as Python, Spotfire, and JMP.
  • Experience analyzing and modeling semiconductor process data.
  • Experience extracting features from manufacturing data and performing mathematical analysis.
  • Experience collecting necessary data from databases using SQL.
  • Ability to provide technical instruction to less-experienced engineers.
  • Intermediate-level or higher Excel skills.
  • Intermediate-level or higher personal computer skills.
  • Japanese proficiency at JLPT N2 level or above.

Responsibilities

  • Design computer systems required to manage and control semiconductor manufacturing equipment.
  • Model equipment to help improve productivity and quality in advanced semiconductor manufacturing.
  • Analyze data for process improvement using statistical analysis techniques.
  • Disseminate and promote mathematical knowledge related to semiconductor processes.

Desired Qualifications

  • Practical experience in mathematical analysis and equipment control in manufacturing.
  • Experience designing schemas for relational databases.
  • Experience modeling using machine learning.
  • Knowledge of mathematical statistics, Python, and JMP.

About the Company

Quest Global

Engineering services, digital transformation, asset management

QuEST Global provides engineering and lifecycle services across aerospace, automotive, energy, healthcare, and transportation, focusing on digital transformation and asset management. It uses edge computing, cloud, AI/ML, and industrial IoT to deliver tailored engineering solutions through long-term partnerships, service contracts, project-based engagements, and strategic collaborations. It differentiates itself with a broad industry footprint, global delivery model, and emphasis on partnerships, talent development, and workplace culture. Its goal is to help clients improve operational efficiency and drive business growth by transforming engineering processes and assets with digital tools and data-driven management.

Company size
10,001+
Company stage
Growth Equity (Venture Capital)
Total funding
$581M
Headquarters
Greenville, SC
Founded
1997

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