Senior Data Analyst

CACI • Washington Dc, DC

4d

About The Position

Data and artificial intelligence hold transformative potential for emergency management—accelerating disaster response, improving resource allocation, detecting fraud, and scaling human capacity during surge operations. As a Senior Data Analyst on our FEMA ITSA 3.0 program, you will lead the enterprise-wide assessment of FEMA's data readiness and responsible AI/automation opportunities, identifying where intelligent systems can deliver measurable mission value while meeting rigorous governance, privacy, and oversight requirements. You'll evaluate data quality, accessibility, governance maturity, and interoperability across FEMA's portfolio to understand what's possible today and what foundational improvements are needed to unlock advanced analytics and AI capabilities tomorrow. Your analysis will go beyond technical feasibility—you'll define mission-focused use cases that connect data science to operational outcomes like workload triage during disasters, surge support automation, fraud prevention, and predictive analytics for resource planning. This role places you at the intersection of data strategy, AI ethics, and mission impact, where your expertise will shape how FEMA responsibly leverages data and automation to serve disaster-affected communities more effectively. Your recommendations will inform enterprise investment in data platforms, governance frameworks, and AI-enabled capabilities that balance innovation with accountability.

Requirements

• Bachelor's degree and 15+ years of experience in analytics, data engineering, data architecture, or AI/ML solution architecture within regulated or government environments
• Demonstrated expertise with data governance frameworks, metadata management practices, and enterprise data strategy development
• Proven experience with standards-based integration approaches including RESTful APIs, event-driven architectures, and data exchange standards
• Ability to translate mission scenarios and operational requirements into measurable analytics outcomes and AI use cases
• Strong understanding of responsible AI principles including fairness, accountability, transparency, ethics, and bias mitigation
• Experience managing risk and oversight requirements in data and AI implementations within compliance-heavy environments
• Exceptional analytical skills with the ability to assess complex data landscapes and identify strategic opportunities
• Strong communication skills; ability to articulate technical data concepts to non-technical mission stakeholders and executives
• Ability to obtain DHS Entry on Duty (EOD) clearance

Nice To Haves

• Familiarity with FEMA Enterprise Data Warehouse (EDW), Operational Data Store (ODS), or FEMA mission systems and data architectures
• Experience enabling cross-agency data interoperability, federal data sharing, or state/local data integration
• Exposure to MLOps practices, model lifecycle management, and AI operations platforms
• Knowledge of responsible AI frameworks from NIST, OMB, or industry standards bodies
• Experience with federal privacy frameworks including Privacy Impact Assessments (PIAs) and System of Records Notices (SORNs)
• Background in emergency management, disaster response, grants management, or social safety net program data
• Hands-on experience with cloud data platforms (AWS, Azure) including data lakes, warehouses, and analytics services
• Proficiency with data science tools and platforms (Python, R, SQL, Spark, Databricks, SageMaker, Azure ML)
• Experience with data visualization and business intelligence platforms (Tableau, Power BI, Qlik)
• Knowledge of geospatial data, GIS systems, and location intelligence relevant to emergency management
• Familiarity with natural language processing, computer vision, or other AI/ML domain applications
• Understanding of federal data governance policies including Federal Data Strategy, OPEN Government Data Act, and CDO Council guidance
• Background in data ethics, algorithmic fairness assessment, or AI explain ability research
• Certifications in data management (CDMP), data governance, or cloud data platforms

Responsibilities

• Evaluate data quality dimensions including accuracy, completeness, consistency, timeliness, and validity across FEMA's systems
• Assess data accessibility, discoverability, and usability for analytics and operational decision-making
• Document data dictionaries, metadata repositories, and data cataloging maturity
• Review data lineage, provenance tracking, and data flow documentation
• Identify data gaps, quality issues, and structural constraints that limit analytics readiness
• Assess data volume, velocity, variety, and veracity characteristics relevant to AI/ML applications
• Map data exchanges, upstream/downstream dependencies, and cross-system data flows
• Assess interoperability constraints including incompatible data models, inconsistent semantics, and format mismatches
• Identify duplicative data entry, redundant data storage, and opportunities for single-source-of-truth architectures
• Review undocumented interfaces, shadow data sharing, and informal data exchange patterns
• Evaluate API maturity for data access and standards-based integration patterns (RESTful APIs, event streaming, data virtualization)
• Recommend standards-based exchange patterns including common data elements, shared vocabularies, and enterprise data models
• Assess data governance maturity including policies, standards, roles, and accountability structures
• Review data stewardship practices, data ownership clarity, and cross-functional governance forums
• Evaluate metadata management, business glossary implementation, and semantic consistency
• Assess master data management approaches and reference data governance
• Review data quality monitoring, issue remediation workflows, and continuous improvement processes
• Evaluate alignment with federal data strategy principles and open data requirements
• Define compelling analytics and automation use cases aligned to FEMA mission priorities and operational pain points
• Develop AI/automation scenarios such as: Workload triage and prioritization during disaster surge operations, Intelligent routing and case assignment to optimize resource allocation, Fraud detection and prevention in grants and assistance programs, Predictive analytics for disaster forecasting, resource pre-positioning, and demand planning, Natural language processing for survivor communication, document processing, and sentiment analysis, Computer vision for damage assessment, geospatial analysis, and infrastructure evaluation, Robotic process automation (RPA) for repetitive administrative tasks
• Identify enabling datasets, required data pipelines, feature engineering needs, and model development requirements
• Assess technical feasibility including data sufficiency, computational requirements, and integration complexity
• Quantify mission value and operational benefits in measurable terms (time savings, accuracy improvement, capacity augmentation)
• Outline governance structures for responsible AI including ethical review boards, bias assessment processes, and human-in-the-loop controls
• Define privacy controls, personally identifiable information (PII) protections, and privacy-enhancing technologies applicable to AI systems
• Address records management requirements for AI-generated decisions and algorithmic transparency
• Establish risk controls including fairness testing, bias mitigation, explain ability requirements, and adversarial robustness
• Develop accountability structures including roles, responsibilities, and decision authority for AI system oversight
• Recommend model validation, performance monitoring, and continuous evaluation frameworks
• Address algorithmic transparency, explain ability requirements, and human review mechanisms for high-stakes decisions

Benefits

• flexible time off
• robust learning resources
• comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior