Data Scientist (Machine Learning)

Location: hirify.global’s Dayuan Site, Taiwan

Company

hirify.global develops materials and solutions for advanced electronics and high-tech industries.

What you will do

• Clean, prepare, and analyze data for engineering, scientific, and business problems.
• Build and validate regression, machine learning, and supervised computer vision models.
• Connect equipment and production data sources through industrial systems, vendor APIs, OPC UA, or PLC/SCADA tags.
• Develop reliable data ingestion pipelines and centralized databases for analytics and model deployment.
• Create descriptive plots and reports and present analytical methods and results to internal clients.
• Collaborate with data engineering, data science, R&D, equipment vendors, and engineering teams to improve data quality and usability.

Requirements

• MS degree or equivalent experience in mechanical engineering, computer science, industrial engineering, electrical engineering, materials science, applied mathematics/statistics, data science, or a related science and engineering field; alternatively, 2+ years of relevant industry experience.
• Strong Python skills for data preparation, regression, plotting, and implementing basic machine learning or supervised computer vision models.
• Basic knowledge of statistics and quality methods, including regression fundamentals, hypothesis testing, statistical process control, and quality checks.
• Working knowledge of SQL and basic NoSQL queries, plus experience designing databases and data schemas for centralized storage and analytics.
• Familiarity with acquiring equipment and process parameters from industrial systems and landing data in databases.
• Effective communication, collaboration, logical problem-solving, and technical presentation skills.

Nice to have

• Design of experiments and quality engineering experience.
• Research experience applying data science to business, engineering, or scientific problems.

Culture & Benefits

• Full-time position within the R&D department.
• Comprehensive pay and benefits package.
• Environment focused on innovation, collaboration, continuous learning, and solving challenging electronics industry problems.