Sr AI Data Scientist - AI Program Office – Division of Information Technology

Job Description - Sr Data Scientist - AI Program Office – Division of Information Technology (R025812) Always verify and apply to jobs on the official Federal Reserve Board career site or through verified Federal Reserve Board social media channels. Sr Data Scientist - AI Program Office – Division of Information Technology - R025812 Primary Location : DC-Washington Employee Status : Regular Overtime Status : Exempt Job Type : Standard Relocation Provided : Yes Compensation Grade Low : FR PAY GRADE 27 Compensation Grade High : FR PAY GRADE 28 Minimum Salary : $140,500.00 Maximum Salary : $210,500.00 Posting Date : Aug 25, 2026 Position Description Minimum Education Bachelor's degree or equivalent experience Minimum Experience 6 Summary Leads statistical and mathematical initiatives to predict future outcomes through the application of machine learning, natural language processing, and conceptual modeling. Uses existing, and makes improvements to, algorithms to test hypotheses through careful and deliberate model design. Leads statistical analysis, modeling, and simulation that leads to actionable decisions. Applies statistical methods to characterize uncertainty using large, complex datasets. Deploys data mining techniques to refine models that optimize decisions and improve scalable and reusable data mining solutions and capabilities that support Division strategic objectives. Leads methods for transforming data into actionable information. Duties and Responsibilities Lead the development of analytic projects and predictive modeling using data mining techniques (e.g. classification trees, bagging, random forests, boosting, cluster analysis, factor analysis, shrinkage methods). Lead the design and optimization of algorithms for matching and pattern recognition using advanced approaches (e.g. locality-sensitive hashing, fuzzy logic). Lead large-scale analytical research projects through all stages; this includes concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report. Design, build, and leverage large and complex data sets while thinking strategically about uses of data, and how data usage interacts with data design. Lead the transformation of large-scale datasets from internal and external systems in a manner suitable for analysis. Lead large-scale data studies and data discovery initiatives targeting for new data sources or new uses of existing data sources. Lead design and implementation of data quality tests and implements new methods to improve statistical inferences of variables across models. Visualize and report data findings using a variety of formats to enhance insights into complex issues. Communicates findings through internal reports, executive summaries, and formal presentations. Establish links across data sources and map intricate interrelationships. Compile, review, and assess information from academic journals, market sources, and other reports to maintain state-of-the-art knowledge in data analysis techniques. Position Requirements FR-27 Minimum Qualifications: Requires a bachelor's degree or equivalent experience plus six years of experience. Must demonstrate knowledge of competence in the application of advanced theoretical and quantitative techniques in Data Science, Statistics, Mathematics, Computer Science, or other quantitative discipline. Experience with analytical and statistical software packages such as R, MATLAB, or SAS. Experience with programming languages such as Python, Java, or SQL preferred. Extensive experience with large datasets. Passionate about data maintenance and data quality control. Excellent analytical and problem solving skills with attention to detail and data accuracy. Strong interpersonal, communication (verbal and written), relationship management, and customer service skills with a focus on working effectively in a team environment. Work cross-functionally to solve complex problems and improve quality and service. Manage multiple projects and work processes in a timely fashion. Perform involved and independent research and analysis. Ability to maintain confidentiality and appropriately handle sensitive information. FR-28 Minimum Qualifications: Requires a bachelor's degree or equivalent experience plus eight years of experience. Must demonstrate knowledge of competence in the application of advanced theoretical and quantitative techniques in Data Science, Statistics, Mathematics, Computer Science, or other quantitative discipline. Extensive experience with analytical and statistical software packages (R, MATLAB, or SAS). Extensive experience with programming languages (Python, Java, or SQL). Extensive experience with large datasets. Passionate about data maintenance and data quality control. Excellent analytical and problem solving skills with attention to detail and data accuracy. Strong interpersonal communication (verbal and written), relationship management, and customer service skills with a focus on working effectively in a team environment. Lead cross-functional teams to solve highly complex problems and improve quality and service. Manage multiple, highly visible projects and work processes in a timely fashion. Lead involved and independent research and analysis. Maintain confidentiality and appropriately handle sensitive information. Remarks The AI Program Senior/Lead Data Scientist bridges R&D innovation and business impact, partnering with technical and business teams to solve the organization's most complex challenges using cutting-edge AI. You will transform business needs into pilots and support their transition into scalable capabilities. Your work will directly support the organization's research and policy mission while also advancing enterprise AI capabilities. Success requires deep AI expertise, strong analytical rigor, and the ability to coordinate efforts across the organization, ensuring R&D innovations translate into measurable business value. Recent and planned work includes retrieval-augmented search over large document collections, agentic workflows that support analysis, and automation of information distillation processes. Key responsibilities: • Partner closely with the AI Program Business Pilots lead to drive delivery of the organization's most complex and high-profile AI initiatives, coordinating with contractors and technical teams, staying hands-on with code, data, and models, setting technical standards, and unblocking barriers. (FR-28: help lead delivery across multiple concurrent consultant workstreams and enterprise-wide initiatives.) • Partner directly with senior business stakeholders and technical teams (engineers, architects, developers) to translate ambiguous business problems into feasible technical solutions and align R&D innovation with business priorities. (FR-28: lead cross-functional teams on highly complex, enterprise-wide challenges.) • Work with the Chief AI Officer on high-profile projects and brief senior Board leadership on AI initiatives, progress, and impact, translating complex technical work into outcomes for executives. • Drive high-impact AI pilots from concept through delivery, then support transitioning successful pilots into scalable, reusable, production-grade capabilities that advance strategic objectives for the Board's business divisions and the enterprise as a whole. (FR-28: manage a portfolio of highly visible AI initiatives and set priorities across concurrent efforts.) • Develop and deploy agentic AI systems and context-engineering approaches, coordinating multiple agents and task workflows to solve complex research and business problems; tune prompts, context, and LLM performance for reliability and accuracy. (FR-28: lead the design of advanced agentic architectures and evaluate emerging AI paradigms for enterprise adoption.) • Leverage AI-assisted development tools (e.g., Claude Code, Codex, Cursor) to accelerate development, refactoring, and debugging while maintaining code quality, security, and compliance standards. (FR-28: establish and scale AI-assisted engineering practices across teams.) • Establish baselines and success metrics for AI initiatives; measure and report realized outcomes against them, including quality control for models and agentic systems in production and the cost of model and infrastructure usage relative to value delivered. • Maintain state-of-the-art expertise by monitoring academic, industry, and open-source advances in data science, machine learning, and AI, including RAG, agentic AI, LLM optimization, and emerging approaches for connecting structured and unstructured data sources to AI systems (e.g., model context protocol (MCP)), and applying them to the organization's mission. The ideal candidate will possess and demonstrate the following desired qualifications: • Expert-level experience in traditional data science techniques, RAG systems, and embedding architectures including hands-on expertise optimizing RAG systems (vector databases, embeddings, chunking, retrieval quality); strong knowledge of natural language processing (NLP) techniques and unstructured data processing; proven track record building production-grade RAG implementations with measurable improvements. (FR-28 requires demonstrated thought leadership and ability to architect enterprise-scale RAG solutions.) • Experience with agentic AI and context engineering including demonstrated ability designing AI systems where agents collaborate to solve complex problems; strong knowledge of prompt engineering, context optimization, and LLM performance tuning; hands-on experience with agent coordination and task workflows. FR-28 requires expertise in advanced agentic architectures and emerging AI paradigms. • Advanced proficiency with AI coding tools including hands-on experience with AI-assisted development tools (Claude Code, Codex, Cursor, or similar); proven ability leveraging AI to accelerate code development, refactoring, and debugging; demonstrated skill integrating AI coding assistants into production workflows while maintaining code quality and security standards. (FR-28 requires track record scaling AI coding practices across teams.) • Advanced data science and experimental rigor with strong proficiency in Python/SQL/R for data engineering, descriptive and inferential statistics, and data manipulation across structured and unstructured sources; ability to design and build large, complex datasets with attention to how intended use shapes data design; demonstrated experience building predictive models, decision engines, and metrics frameworks; proven ability synthesizing complex data into actionable insights; ability to work with economic data, financial datasets, and policy-relevant information to support research and policy analysis. • Experience building strategic, cross-functional business partnerships with track record working directly with senior business stakeholders and technical teams (engineers, architects, developers) on high-impact AI initiatives to ensure feasibility and implementation; proven ability leading pilots that deliver measurable outcomes; skill translating ambiguous business problems into innovative technical solutions that align R&D efforts with business priorities; ability to work independently and influence without authority on complex challenges. • Experience training and leading by example with ability to teach staff effective use of AI tools through hands-on demonstrations and mentoring; track record building organizational AI literacy and fostering a culture of continuous learning. (FR-28 requires experience developing enterprise-wide AI education strategies.) • Exceptional communication skills with ability to articulate complex AI capabilities to executive audiences while effectively collaborating with technical practitioners; skill visualizing data and building a clear narrative from complex analysis for internal reports, executive summaries, and formal presentations; proven experience building organizational buy-in for AI initiatives across business and technical stakeholders. • AI governance expertise including deep understanding of model validation, bias detection, and compliance frameworks in production AI systems. • Background or strong interest in economics, finance, or Federal Reserve mission areas (monetary policy, financial stability, banking supervision, payments, consumer protection); ability to understand domain-specific challenges and translate them into AI opportunities. • Recognized expertise through publications, patents, conference presentations, or significant open-source contributions in agentic AI, RAG systems, or LLM optimization. • Experience in highly regulated environments (government, financial services) is desired. *U.S. CITIZENSHIP REQUIRED* This position is located in Washington, DC. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment on the basis of race, color, religion, sex, pregnancy, national origin, age, disability, genetic information, or application, membership, or service in the uniformed services.