Digital Engineer - Dayuan

Job Responsibilities:

• Hands-on experience in data science practices such as data cleaning, regression, and building machine learning and computer vision models.
• 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.
• 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