Senior Data Scientist - Artificial Intelligence

Senior Data Scientist (Artificial Intelligence) Federal Reserve Board – Division of Consumer and Community Affairs (DCCA) Company: Diverse Agile Solutions (DAS) Location: Washington, DC (Hybrid Preferred) | Remote Considered Job Type: Full-Time Consultant Clearance/Work Authorization: U.S. Citizenship Required About Diverse Agile Solutions Diverse Agile Solutions (DAS) is a certified Minority Business Enterprise (MBE) specializing in delivering innovative technology solutions and highly skilled IT professionals to federal, state, and commercial organizations. Our expertise spans Artificial Intelligence, Cloud Engineering, Data Analytics, Agile Transformation, DevSecOps, Cybersecurity, Enterprise Architecture, and Digital Modernization. At DAS, we help organizations solve complex business challenges through emerging technologies while fostering innovation, collaboration, and continuous learning. Position

Diverse Agile Solutions is seeking a Senior Data Scientist (Artificial Intelligence) to support the Federal Reserve Board's Division of Consumer and Community Affairs (DCCA) as part of its newly established AI Lab. This is an exciting opportunity to help build next-generation Artificial Intelligence capabilities that improve consumer protection, regulatory oversight, community development, and operational efficiency through Generative AI and Machine Learning. The ideal candidate is a full-stack AI practitioner capable of owning the complete AI lifecycle—from research and experimentation to application development, deployment, monitoring, and production support. You will work closely with economists, attorneys, analysts, and senior leadership to design intelligent solutions that deliver measurable business value.

Artificial Intelligence & Machine Learning Development • Research, design, and develop innovative AI and Machine Learning solutions supporting DCCA initiatives • Build proof-of-concept AI applications and transition successful prototypes into production • Develop Generative AI solutions using Large Language Models (LLMs) • Design Retrieval-Augmented Generation (RAG) architectures • Implement prompt engineering strategies for enterprise AI applications • Fine-tune and evaluate foundation models for domain-specific use cases • Develop NLP solutions including: • Text classification • Named Entity Recognition (NER) • Information extraction • Document summarization • Semantic search • Apply supervised, unsupervised, deep learning, and statistical modeling techniques • Evaluate emerging AI frameworks and technologies for enterprise adoption Full-Stack AI Application Development • Build production-ready AI applications using: • Python • Streamlit • Dash • Flask • R Shiny • Develop intuitive dashboards and visual analytics applications • Create interactive data visualizations using: • Plotly • Matplotlib • Seaborn • Tableau • Power BI • Translate complex analytical findings into actionable business insights Deployment & MLOps • Deploy AI and ML applications into cloud environments • Containerize applications using Docker • Build CI/CD pipelines for AI deployments • Implement model monitoring and observability • Create automated retraining pipelines • Manage model versioning and lifecycle management • Optimize API integrations and AI inference costs • Troubleshoot and maintain production AI applications • Collaborate with Cloud Engineers and Infrastructure teams Agile Collaboration • Participate in Agile ceremonies including: • Sprint Planning • Daily Standups • Sprint Reviews • Retrospectives • Partner with business stakeholders to identify AI opportunities • Translate business