AI and Data Science Solutions Lead, Asia Pacific

About the Role The AI and Data Science Solutions Lead for Asia Pacific will research theories and cutting‑edge technologies in Artificial Intelligence (AI) and Machine Learning (ML) to contribute to realizing advanced intelligent manufacturing platforms. This role involves building and leading a data science and engineering team in Schaeffler Asia Pacific, driving the development of data analytics and AI solutions for Schaeffler's Industrial and Automotive business, and supporting SHARE at NTU. Job Responsibilities Drive the evolution of digital services and solutions with a focus on data science solutions and AI activities supporting both AP IT & Digitalisation and SHARE at NTU. Lead the development of data analytics infrastructure and build the service platform. Collaborate with product managers and group IT to align Schaeffler's digital solution technology roadmaps with new data analytics solutions. Work independently or in a small team with product engineering and third parties to drive development and rapid prototyping of new solutions and applications leveraging emerging data science and AI technologies. Act as a domain and subject matter expert for newly developed data analytics solutions, supporting sales efforts with technical presentations and demonstrations. Support organization building activities in recruiting and training. Attend trade shows and industry meetings; stay abreast of evolving data solution trends. Lead research activities, solve challenging manufacturing process problems with AI, and present visions for future AI research. Participate in and lead AI research collaborations with other Research & Development (R&D) organizations in Asia Pacific. Work closely with the Asia Pacific Chief Information Officer and the Director for SHARE at NTU on R&D activities and translate them into Digital business and solutions for Schaeffler. Achieve state-of-the-art methodologies in fields including, but not limited to: Anomaly Detection based on learning theories (Semi/Self/Un-supervised learning) (2D/3D) Human Pose estimation , Behaviour classification , Abnormal behaviour detection , Person Re-identification Online/Continual Learning , Lifelong Machine Learning Multivariate data analytics ( Recurrent neural network , pattern recognition ) Job Requirements Minimum of a Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field pertaining to artificial intelligence , machine learning , data science , or computational analysis . A Master's or Ph.D. in this field is advantageous. Candidates with outstanding research achievements and experience in leading research organizations in AI/ML will be preferred. Minimum of 5-8 years of relevant industry experience in AI/ML research is preferred. Comfortable with research methodologies to address abstract business and production problems with extreme precision; able to gain data-driven insight and support business. Expert knowledge in core data science modeling , familiar with common machine learning methods (e.g., clustering , classification , regression ), and experience in training and deploying models in production. Expertise in architecting data solutions with the latest hardware and software engineering competencies, focusing on cloud based data warehouse architecture and technologies, BI tools , and cloud capabilities . Hands‑on experience in programming and scripting skills for creating data solution prototypes, specifically Node.js and Python , is a plus. Previous experience in mobile application development is also a plus. Travel will be required for interfacing with global customers, sales channels, engineering, systems, and product development teams. #J-18808-Ljbffr