About the role
Job Family: Data Science & Analysis Travel Required: None Clearance Required: Ability to Obtain Public Trust What You Will Do: Design, develop, implement, and maintain AI and machine learning solutions that improve healthcare, public health, biomedical research, and operational decision-making. Identify opportunities to improve organizational efficiency by applying AI, automation, and advanced analytics to streamline business processes, reduce manual effort, and enhance workforce productivity. Design and implement AI-enabled workflow solutions for document processing, knowledge management, literature reviews, information retrieval, case management, reporting, decision support, and other operational functions. Develop Generative AI (GenAI) solutions using large language models (LLMs), retrieval augmented generation (RAG), semantic search, vector databases, AI agents, and prompt engineering techniques. Develop predictive, classification, clustering, natural language processing (NLP), computer vision, and other machine learning models using structured, semi-structured, and unstructured data. Develop scalable data science pipelines using Python, SQL, Spark, and cloud-native analytics platforms. Evaluate, validate, and monitor AI models for performance, explainability, fairness, bias, reproducibility, and operational effectiveness. Collaborate with epidemiologists, researchers, engineers, program staff, and business stakeholders to identify AI use cases, prioritize opportunities, and translate business needs into production-ready AI solutions. Develop dashboards, visualizations, technical documentation, presentations, and demonstrations that communicate AI capabilities and analytical findings to technical and non-technical audiences. Support deployment, monitoring, and continuous improvement of AI and machine learning solutions using modern MLOps and DevSecOps practices. Apply responsible AI principles, governance, privacy, security, and human-in-the-loop review throughout the AI lifecycle. Mentor junior team members and provide technical leadership, solution design, and code reviews as appropriate. What You Will Need: Bachelor's degree in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Statistics, Public Health, or related field (or equivalent professional experience). Experience developing AI and machine learning solutions using Python and common data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar frameworks. Experience applying AI to automate workflows, improve business processes, or enhance operational efficiency. Experience developing Generative AI applications using large language models (LLMs), prompt engineering, retrieval augmented generation (RAG), or similar techniques. Experience developing statistical models, predictive analytics, classification, clustering, regression, or natural language processing (NLP) solutions. Strong SQL skills and experience working with relational databases and cloud-based data platforms. Experience preparing, integrating, transforming, and analyzing structured and unstructured data to support AI, machine learning, and advanced analytics solutions. Experience deploying AI or machine learning solutions into production environments. Understanding of responsible AI principles, model evaluation, explainability, governance, and human oversight. Experience working in Agile software development environments and fast-paced, matrixed organizations Strong analytical, problem-solving, written, and verbal communication skills. Ability to work independently and collaboratively in multidisciplinary technical teams. U.S. Citizenship required. Ability to obtain and maintain a Public Trust or higher federal security clearance, as required. What Would Be