Holistic responsibility for CT related data analytics application and data innovation projects, including product design, data modelling, data validation, and product deployment, and contribute on CT product development specially on stability and utilization. · Act as the data science owner for business-critical analytics applications. Translate CT business objectives into well-defined data science problems, assess data feasibility, and define appropriate analytical or machine learning approaches. · Develop and validate statistical and machine learning models for use cases such as utilization analysis, reliability prediction, anomaly detection, and early warning of quality issues based on installed-base, production, and R&D test data. · Analyze data across the CT end-to-end data chain, including PLM process data, using data mining, process mining, and visualization to identify patterns, root causes, risks, and optimization opportunities. · As a product owner of business-critical data analytics applications, supporting the analysis of business objectives, assess the problems need to be solved using data analytics methods and communicate the requirements to CT business stakeholders. · Other tasks assigned by superiors. Working closely with SSME CT PLM and HC DI CT R&D ES to design and develop algorithm for big data analysis and analyze business data. · Internal: Other CT R&D colleagues, CT business stakeholders · External: Big data consultants/service provider Experience · Experience in the fields of data analysis with successful execution of data science projects; · Strong understanding and experience in execution of data science workflows like CRISP-DM, industry standards and trends in the specialist field; Solid understanding of Machine Learning (supervised and unsupervised learning, NLP, explainable AI) and exploratory data analysis and feature engineering; Experience in Deep Learning (TensorFlow, PyTorch) would be a plus is plus; · Experience in Visual Analytics, building data-driven applications for end users with BI tools (Qlik, Power BI). Education Master degree or above in Information Science, Data Science, Mathematics, Physics, AI, etc.