- Location
- AP-TW-Dayuan (EL), Taiwan
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Education
- Source
- Workday
Description
Are you looking to power the next leap in the exciting world of advanced electronics? Do you want to help solve problems that drive success in the rapidly evolving technology and connectivity landscape? Then bring your problem-solving, passion, and creativity to help us power the next leap in electronics.
At Qnity, we’re more than a global leader in materials and solutions for advanced electronics and high-tech industries – we’re a tight-knit team that is motivated by new possibilities, and always up for a challenge. All our dedicated teams contribute to making cutting-edge technology possible. We value forward-thinking challengers, boundary-pushers, and diverse perspectives across all our departments, because we know we play a critical role in the world enabling faster progress for all. Learn how you can start or jumpstart your career with us.
Qnity is accepting applications for a position as a Data Scientist. This position will be at Qnity’s Dayuan Site, Taiwan. This is an exciting opportunity to join a growing team that plays a vital and dynamic role in the company’s R&D department.
A strong candidate will have hands-on experience in data science practices such as data cleaning, regression, and building machine learning and computer vision models. The applicant should have fluent coding skills in Python, with the ability to build databases, prepare data for analysis, develop and validate models, create descriptive plots and reports, and communicate methods and results to business partners. Beyond these technical skills, the job requires an organized worker who can solve challenging problems with a series of logical steps, collaborate with our data engineering/data science/R&D teams to query data and deploy solutions, and continuously improve data quality and usability.
Work with equipment/production vendors and engineering teams to connect equipment data sources and build reliable data ingestion pipelines to store parameters and process signals into centralized databases for downstream analytics and model deployment.
Qualifications:
MS degree+ (or equivalent experience) in Mechanical Engineering, Computer Science, Industrial Engineering, Electrical Engineering, Materials Science, Applied Math/Statistics, Data Science, or a related science & engineering field; or 2+ years of relevant industry experience
Strong coding skills in Python including data preparation, regression, plotting, and implementing basic machine learning or supervised computer vision models (e.g., clustering, classification)
Basic knowledge of statistics and quality methods (e.g., regression fundamentals, hypothesis testing basics, SPC, and quality checks); DOE and quality engineering experience is a plus
Working knowledge of SQL and basic NoSQL (e.g., MongoDB) queries; experience designing/building databases and data schemas for centralized storage and reliable analytics (e.g., data lake/warehouse)
Familiarity with acquiring equipment/process parameters from industrial systems (e.g., OPC UA, PLC/SCADA tags, or vendor APIs) and landing the data into a database
Research experience in applying data science to solve business, engineering, or scientific problems
Self-learning with the intellectual curiosity to keep abreast of advances in the field, grow data science expertise, and refine grasp of internal business operations over time
Effective interpersonal skills for communicating technical concepts to non-experts, collaborating with team members, and confidently presenting data analysis results to internal clients
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Qnity is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. If you need a reasonable accommodation to search or apply for a position, please visit our Accessibility Page for Contact Information.
Qnity offers a comprehensive pay and benefits package. To learn more visit the Compensation and Benefits page.
We use Artificial Intelligence (AI) to enhance our recruitment process.
