Sr. Capability Implementation Manager, Machine Learning
Update frameworks for ETS capabilities based on recent developments in machine learning, lead design and implementation processes for transition of research to operations.
Location: Princeton, NJ
Summary: The candidate for this position will be responsible for designing and implementing processes related to the transition of research projects to operational products and services. They will update frameworks for ETS capabilities based on recent developments in machine learning. They will communicate with potential and current clients about the application of ETS Capabilities.
BASIC FUNCTIONS AND RESPONSIBILITIES
Provide technical skills in executing projects and initiatives related to the application of machine learning to problems in the educational domain. Manage the development and evolution of capabilities based on machine learning, natural language processing and speech technologies which are used to improve assessments, learning tools and test development practices.
Coordinate with Natural Language Processing and Speech scientists to incorporate new functionality for evaluating student responses and other educational texts into ETS Capabilities.
Apply technical and software engineering skills in executing projects and capability development in support of educational products and services. Incorporate best practices in machine learning into the development and evaluation frameworks for ETS capabilities.
Develop and monitor project budgets for work related to capability development and application.
Develop and maintain project and capability documentation in the form of external communication materials, software documentation, and technical reports.
Communicate with internal and external parties to assess the feasibility of applying ETS capabilities using machine learning. Assess the needs of potential or current clients, the fit with ETS capabilities, and the potential for application of these capabilities with or without additional development.
Conduct applied studies functioning as an expert in the major facets of the projects; respond as a subject matter expert in presenting the results of acquired knowledge and experience. Consult and collaborate on problems arising from research and/or testing programs, or corporate management concerns.
Serve as an expert resource on ETS capabilities for internal and external audiences, conducting demonstrations, participating in business discussions related to their application, and drafting descriptive materials.
A Master's degree in a field with strong emphasis on quantitative data analysis, computer science, or statistical learning theory is necessary. A PhD in a related field is highly desirable.
A very strong statistical background and a solid experience with machine learning algorithms are required. Evidence of substantive contributions to the development and application of software systems using machine learning or data mining are also necessary. Candidates must have experience in communicating the functionality and range of application of machine learning systems to both technical and non-technical audiences. Experience programming in computer languages such as Python, Java, and R is highly desirable.
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