Senior Data Scientist - Artificial Intelligence

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., * 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 requirements into scalable AI solutions
• Present findings to executive leadership and technical teams
• Document code, methodologies, and technical decisions
• Mentor team members and contribute to the growth of DCCA’s AI practice

Governance & Responsible AI

• Develop AI solutions aligned with federal security and governance standards
• Support FISMA, Privacy Impact Assessments, and ATO documentation
• Apply Responsible AI principles including:
• Fairness
• Bias detection
• Explainability
• Transparency
• Collaborate with security and compliance teams throughout the AI lifecycle, * Large Language Models (GPT, Llama, Nova)
• LangChain
• LlamaIndex
• Prompt Engineering
• Vector Databases
• Semantic Search
• AWS AI Services including:
• Amazon Bedrock
• SageMaker
• Comprehend
• Rekognition
• Transcribe
• AWS deployment services:
• EC2
• ECS
• Lambda
• S3
• CloudWatch
• Databricks
• Infrastructure as Code:
• Terraform
• CloudFormation
• MLOps
• Model Monitoring
• Automated Retraining
• Responsible AI
• AI Explainability
• Multi-modal AI
• AWS Certifications
• Experience handling regulated or sensitive data, * Scikit-learn
• spaCy
• XGBoost
• LangChain
• LlamaIndex
• Streamlit
• Dash
• Flask
• R Shiny

Cloud & DevOps

• AWS
• Docker
• Kubernetes
• CI/CD
• Git
• Terraform
• CloudFormation

Visualization

• Tableau
• Power BI
• Plotly
• Matplotlib
• Seaborn
• ggplot2

• U.S. Citizenship
• Bachelor’s degree in Computer Science, Data Science, Statistics, Machine Learning, or a related field
• Master’s degree preferred
• Minimum 6 years of professional experience developing, deploying, and maintaining AI/ML applications
• Expert proficiency with Python or R
• Experience building production AI applications
• Experience deploying Machine Learning solutions into cloud environments
• Strong knowledge of:
• Machine Learning
• Deep Learning
• Natural Language Processing
• Generative AI
• Experience with:
• Scikit-learn
• spaCy
• XGBoost
• Experience developing interactive applications using:
• Streamlit
• Dash
• Flask
• R Shiny
• Experience creating dashboards and visualizations using:
• Tableau
• Power BI
• Plotly
• Matplotlib
• Seaborn
• Experience with containerization and CI/CD
• Strong statistical modeling and analytical skills
• Excellent written and verbal communication skills
• Ability to independently deliver solutions from concept through production, Candidates with experience in one or more of the following are highly encouraged to apply:
• Federal Government or Regulatory Agency experience
• Financial Services or Banking
• Consumer Finance
• Banking Supervision
• Agile methodologies (Scrum, Kanban), * Python
• R
• SQL

AI / Machine Learning

• Generative AI
• Large Language Models (LLMs)
• Machine Learning
• Deep Learning
• NLP
• RAG
• Prompt Engineering
• Semantic Search
• Fine-Tuning

• Competitive compensation
• Exciting federal technology programs
• Opportunities to work with cutting-edge AI technologies
• Collaborative and innovative culture
• Professional development and certification support
• Exposure to enterprise-scale cloud and AI platforms
• Opportunity to help shape the future of AI in the federal government