Senior Data Scientist

Qnity is accepting applications for a position as a Data Scientist – CFD & Multiphysics Modeling. This position will be based at Qnity’s Hsinchu Site I, Taiwan. This is an exciting opportunity to join a growing Data Science team that plays a vital and dynamic role in Qnity’s R&D organization. A strong candidate will have expertise in data science practices such as data cleaning, regression, machine learning, deep learning, large language models, and computer vision. The applicant should have fluent coding skills in Python, with the ability to prepare data for analysis, build models, create descriptive plots and reports, and understand deep learning models, including large language models and computer vision models. Experience or interest in CFD-enabled and multiphysics modeling for wet-chemistry and deposition processes would be valuable for this role, particularly in semiconductor and electronics applications. The candidate will work with R&D, process engineering, and data engineering teams to translate experimental, modeling, and simulation insights into actionable process, formulation, and equipment recommendations. Beyond technical skills, the role requires an organized problem-solver who can structure complex problems into logical steps, communicate methods and results clearly to business and technical stakeholders, and collaborate across functions to deliver practical solutions.

- A PhD degree, or a Master’s degree with at least 2 years of relevant experience, in a science or engineering technical field. - Strong coding skills in Python, including data preparation, regression, model development, visualization, and reporting. - Formal education in statistics, including regression, hypothesis testing, and experimental data analysis.

- Experience applying data science to solve business, engineering, or scientific problems, with the ability to convert ambiguous technical questions into structured analytical workflows. - Basic competency with SQL, MongoDB or similar database queries, and visualization prototyping. - Self-learning mindset and intellectual curiosity to keep abreast of advances in data science, grow technical expertise, and refine understanding of internal business operations over time.

- Exposure to simulation automation, model calibration, design of experiments, surrogate modeling, or physics-informed machine learning is preferred. - Experience with cloud computing or scalable computing environments, such as Microsoft Azure, for data science or simulation workflows. Join our Talent Community to stay connected with us!