Main Tasks:
- Data-driven modelling as part research and development project teams. This could include modelling and analysis for exploratory, predictive, or explanatory objectives, as well as experimental design support, as required.
- Apply and adapt modern machine learning (ML) techniques to scientific problems.
- Identify innovation opportunities and conduct methodological research to realize benefits from statistics/ML in chemical industry R&D.
- Deliver data analytics solutions to internal customers via software packages, dashboards, and/or web apps.
- Develop innovative technical solutions via close collaboration with other data scientists, scientific modelers, and researchers in advanced materials.
- Actively exchange knowledge, ideas, and solutions with colleagues from different regions.
- Document and present research results, as well as observe and evaluate current industry trends.
Requirements:
- MSc or higher in a STEM discipline with a strong quantitative background.
- Formal training in statistics and/or machine learning fundamentals, or deep understanding obtained through extensive practical experience and self-study in these areas.
- Hands-on experience with common ML models (random forests, deep learning, RNN, logistic regression, etc.).
- Strong programming skills in languages such as Python or R.
- Meaningful experience with any of the techniques, platforms, and technologies common to industrial data science (deep learning libraries, workflow and deployment solutions, databases, containers, version control & continuous integration, autoML, parallel/cloud computing, etc.) will be a plus.
- You are motivated by continuous learning of new methods and techniques in data science.
- A clear interest in applying your talents to problems in science and engineering.
- Good communication skills and teamwork, as well as fluency in spoken and written English.
请时刻警惕任何可能的招聘欺诈行为！请注意，巴斯夫绝不会在任何情况下向候选人以任何形式收取任何费用。