Works effectively with peers, management, operations groups, and outside organizations. Work across multiple cross-functional teams in high visibility roles to prototype end-to-end data solutions. Work on developing and tuning robust machine learning and data-science models to previously unsolved domain problems. Identify and communicate to the community of stakeholders about upcoming technologies. Ensure that data science code is maintainable, scalable, and deployable in modern computational stack. Bring the best software development practices to the data science team and help them accelerate their work. Together with the DevOps team, choose the best operational architectures. Look for performance improvement and decide which machine learning technologies will be used in the production environment 1-5 years of experience in applied technology development, applied research of deep learning in physical-systems, or a combination of both. Experience in data-driven modeling using modern data science techniques from statistics and machine learning. Hands-on experience in modern Machine learning frameworks such as TensorFlow and PyTorch, with a strong emphasis on full computer system design. Expertise with one or more of the AI, Data Science or Machine Learning solution suite from major cloud providers. Computer programming skills for early-stage prototyping and development towards the production of suitable software to be deployed in modern system stack (cloud, containers, etc.) Advanced ability to work with data-driven models, including parameter tuning, feature engineering and other associated tasks. Experience on robust model development that honors business and engineering requirements in terms of decision making and decision support. PhD degree in a Scientific or Engineering discipline with strong emphasis on the mathematics fundamentals of Data Science, Artificial Intelligence. Engineering training at the Undergraduate level is a plus. Team-oriented behaviors and skills and comfortable taking technology and scientific risks to explore solutions and approaches outside traditional viewpoints and guide others towards such vision. Very good written and verbal communication skills. Strong ability to communicate advanced data science and AI concepts to others with a background in traditional engineering disciplines and/or pure business background. Proficiency in programming languages such as Python, R, or others related to modern data-driven products for IoT/Edge
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