Lead Data Scientist

Job Summary: We are seeking a Subject Matter Expert (SME)-level Lead Data Scientist to leverage cutting-edge techniques to extract insights and patterns from large and complex datasets for the U.S. Census Bureau's Decennial Transformation and Application Modernization (DTAM) effort. This role provides technical and management leadership on major advanced data science assignments, developing advanced algorithms, models, and frameworks using machine learning, deep learning, natural language processing, and generative AI / large language models. The Lead Data Scientist ensures AI/ML products are safe, trustworthy, explainable, and compliant with the NIST AI Framework and Census Bureau policies. Decision-making and domain knowledge may have a critical impact on overall program implementation. May supervise others. Responsibilities: Develop advanced algorithms, models, and frameworks leveraging machine learning, deep learning, neural networks, natural language processing, and generative AI / large language models (LLMs) Manage all activities to align with current advanced analytics and data science standards as defined by Decennial, the USCB, and industry best practices Support the transition of advanced analytics and data science capabilities from pilot to production and maintain them in the production environment Develop descriptive and predictive models for survey efforts, including time series, anomaly detection, semi-supervised, active, and reinforcement learning frameworks Conduct data cleaning, filtering, transformation, and feature engineering to create machine-learning-ready datasets Create, maintain, and use synthetic data to support the full lifecycle of advanced data science Follow AI regulation and ethical principles in accordance with the NIST AI Framework to manage AI risk and ensure model trustworthiness Ensure AI products are safe, secure, explainable, interpretable, privacy-enhanced, fair, valid, reliable, accountable, and transparent Develop, document, and test prototypes and proofs-of-concept leveraging advanced data science Evaluate trained models with multiple performance metrics, appropriate test sets, and learning curves Develop and maintain data science documentation, including analysis plans, technical reports, user manuals, and best-practice templates Education and Experience PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field - mandatory 15+ years of experience providing technical and management leadership on major data science assignments (SME level) Required Skills Expert proficiency in Python, R, SAS, and SQL and associated data science libraries and tools Demonstrated experience developing and operationalizing ML, deep learning, NLP, and generative AI / LLM models Strong background in predictive modeling, time series analysis, anomaly detection, and feature engineering Experience creating and using synthetic data and privacy-preserving data techniques Working knowledge of the NIST AI Framework and responsible/ethical AI practices Desired Skills: Experience transitioning data science capabilities from pilot to production (MLOps / LLMOps) Familiarity with differential privacy, federated learning, and secure multi-party computation Experience with large-scale federal statistical or survey data programs Excellent written and verbal communication skills, including manuscript preparation and executive briefing to senior Government stakeholders