Research Scientist

AI-Based Workforce Support Tools Developer The position will support the research, development, prototyping, and evaluation of Artificial Intelligence (AI)-based workforce support tools designed to improve the efficiency of regulatory analysis and rulemaking processes. The successful candidate will contribute to the continued development of AI tools that assist in identifying potential FAR/DFARS changes resulting from National Defense Authorization Acts (NDAAs) and other policy drivers, supporting the preparation of draft regulatory language for human review, analyzing and summarizing public comments, and developing related AI-enabled decision-support capabilities. The position requires a combination of applied Artificial Intelligence, Natural Language Processing (NLP), text analytics, data visualization, and rapid software prototyping skills. The individual will work with researchers and subject-matter experts to translate operational and regulatory requirements into functional AI prototypes and analytical tools. Responsibilities The successful candidate will be expected to: Develop, implement, and refine AI and Natural Language Processing techniques for analyzing regulatory, legislative, policy, and other large-scale textual datasets. Support the development of AI tools for identifying relevant provisions and potential changes to FAR/DFARS regulations resulting from NDAAs and other regulatory drivers. Develop methods for comparing, classifying, extracting, and summarizing information from complex regulatory and policy documents. Support the development and evaluation of AI-assisted approaches for generating draft regulatory content for subsequent review and validation by human subject-matter experts. Develop text analytics approaches for organizing, categorizing, and summarizing public comments associated with proposed FAR/DFARS changes. Design and implement data visualization methods and interactive analytical outputs that communicate results from text analytics and NLP models to end users. Rapidly develop, test, and modify software prototypes to evaluate alternative AI approaches and respond to evolving user requirements. Integrate AI/NLP models, analytical methods, and visualization components into functional prototype tools. Work with researchers, developers, and subject-matter experts to understand user needs, existing workflows, and time-intensive regulatory processes that may benefit from AI-enabled support. Support pilot testing and evaluation of prototype tools with users, including the collection and analysis of performance and usability metrics. Evaluate the effectiveness of AI-enabled tools in improving workflow efficiency, reducing manual analytical effort, and supporting human decision-making. Document methodologies, algorithms, prototype capabilities, testing procedures, and analytical results. Contribute to the transition of successful research prototypes toward operationally relevant workforce support tools. Required Qualifications Master's degree in Artificial Intelligence, Computer Science, Data Science, Machine Learning, Computational Linguistics, Systems Engineering, or a closely related technical field with a significant AI or data analytics component. Demonstrated knowledge of Artificial Intelligence and Machine Learning methods. Demonstrated experience implementing Natural Language Processing and text analytics techniques. Experience working with unstructured and semi-structured textual data, including document classification, information extraction, semantic analysis, text similarity, summarization, or related techniques. Experience developing data visualizations for communicating results from text analytics, NLP, or other data-intensive analyses. Strong programming skills and demonstrated ability to rapidly develop, test, debug, and modify analytical code and software prototypes. Proficiency with Python or comparable programming languages commonly used for AI, machine learning, and data analytics. Ability to translate research concepts and user requirements into implementable analytical methods and prototype capabilities. Strong analytical, problem-solving, and technical communication skills. Ability to work effectively in a multidisciplinary research and development environment. Preferred Qualifications Experience with large language models (LLMs), transformer-based NLP models, embeddings, retrieval-augmented generation (RAG), or related generative AI technologies. Experience developing AI applications involving document comparison, semantic search, information retrieval, automated summarization, or question-answering systems. Familiarity with visualization frameworks and approaches for presenting complex textual or document-based analytical results. Experience with rapid prototyping and iterative development of AI-enabled applications. Experience evaluating AI systems using quantitative performance metrics and human/user-centered evaluation methods. Familiarity with regulatory, legislative, acquisition, government, or policy-oriented textual datasets is desirable but not required. Stevens Institute of Technology