PENDING CONTRACT AWARD WINTER 2026Position SummaryCredence has an upcoming need for a Data Analytics and AI Integrator serves as the senior contractor authority for data analytics, automation, artificial intelligence, and machine learning initiatives across the SAF/CN support program. This position will Lead integration across cybersecurity, compliance and policy, business enterprise management, enterprise IT, and program-management activities. This position will establish a coordinated delivery approach, align initiatives with Government data and responsible-AI standards, and ensure that analytics and AI solutions are secure, explainable, reusable, measurable, and ready for Government decision or operational adoption.
Primary ResponsibilitiesEnterprise Leadership, Governance, and Integration- Lead and integrate contractor Data and AI execution across SAF/CNZ, SAF/CNB, SAF/CNS, and program-management activities, coordinating priorities with the applicable division leads and the Contractor Program Manager.
- Serve as the principal contractor interface for cross-cutting Data and AI matters and coordinate with SAF/CND, SAF/CTO, system owners, Authorizing Officials, portfolio managers, infrastructure teams, and other stakeholders to align with enterprise standards and avoid duplicative or conflicting solutions.
- Establish and maintain an integrated Data and AI roadmap, use-case inventory, prioritization process, dependency map, and delivery backlog that connect initiatives to mission outcomes, performance requirements, authoritative data sources, and accountable owners.
- Lead cross-functional teams of data analysts, data engineers, data architects, cybersecurity specialists, cloud architects, automation developers, and mission subject matter experts; set priorities, resolve dependencies, review quality, and elevate delivery, security, data, or adoption risks.
- Brief senior DAF leaders on Data and AI opportunities, portfolio status, measurable benefits, resource implications, risk, adoption barriers, and recommended decisions.
Data Analytics, Engineering, and Decision Support- Design and oversee analytics products that integrate authoritative cybersecurity, compliance, portfolio, architecture, asset, financial, operational, and infrastructure data to provide timely, decision-quality insight.
- Establish repeatable practices for data discovery, profiling, validation, cleansing, reconciliation, metadata management, lineage, quality measurement, access-control mapping, and authoritative-source designation.
- Guide development of reusable data models, taxonomies, data dictionaries, data pipelines, application programming interfaces, dashboards, scorecards, and automated workflows using Government-approved platforms.
- Apply advanced analytics to identify trends, anomalies, systemic control failures, aging actions, cost and capacity drivers, modernization candidates, and mission-risk priorities, with qualified human validation before Government use.
- Translate analytic findings into clear executive briefings, decision papers, implementation recommendations, and measurable performance indicators.
AI/ML Strategy, Delivery, and Responsible Use- Identify and assess AI/ML opportunities across cyber compliance and auditing, eMASS and workflow automation, policy comparison, business-process optimization, portfolio and investment analysis, forecasting, architecture metadata quality, asset and license management, and enterprise IT modernization.
- Develop business cases and implementation recommendations addressing mission value, data readiness, security, privacy, records management, technical maturity, interoperability, scalability, cost, workforce impact, and acquisition or licensing implications.
- Lead approved pilots and implementations through data preparation, model or service selection, evaluation-criteria definition, testing, human-in-the-loop control design, deployment planning, user adoption, and post-deployment monitoring.
- Establish and maintain model inventories, registrations, model cards, provenance records, evaluation and bias-assessment results, human-oversight controls, and monitoring for accuracy degradation and model drift.
- Ensure all AI-assisted output is reviewed by qualified personnel and that Government data is used only with approved services, models, environments, classifications, and handling controls.
AI Security, Authorization, and Data Protection- Integrate security and authorization considerations from inception, including AI/ML system architecture and data-flow analysis, authorization boundaries, control allocation, inherited controls, evidence requirements, and residual-risk documentation.
- Address training and inference data integrity, provenance, model versioning, adversarial inputs, prompt injection, output validation, endpoint access, secrets management, supply-chain risk, and post-deployment monitoring.
- Apply data-level protection through classification-aware tagging and handling, encryption, least privilege, attribute-based access control, privacy safeguards, records-management controls, and Zero Trust principles.
- Assess reuse of existing Government-licensed analytics, automation, cloud, and AI platforms before recommending new acquisition, and avoid unnecessary vendor lock-in or proprietary dependencies.
Requirements- Active TS/SCI security clearance.
- Bachelor's degree or equivalent combination of education, professional training, and directly relevant experience in data science, analytics, computer science, information systems, engineering, cybersecurity, mathematics, operations research, or a related discipline.
- At least 12 years of progressively responsible experience in data analytics, data engineering or architecture, AI/ML, automation, enterprise IT, cybersecurity analytics, digital modernization, or a closely related field.
- Demonstrated experience leading multidisciplinary technical teams and coordinating enterprise initiatives across multiple organizations or mission areas in a complex Federal, DoW/DoD, DAF, or comparably regulated environment.
- Demonstrated ability to take Data or AI initiatives from use-case definition and data-readiness assessment through design, pilot, evaluation, implementation, governance, and performance monitoring.
- Working knowledge of responsible-AI, data governance, cybersecurity, privacy, records management, cloud, and Zero Trust principles sufficient to integrate specialist inputs and advise senior leaders.
- Experience developing or overseeing executive dashboards, analytical models, automated workflows, data pipelines, technical assessments, strategies, roadmaps, governance artifacts, and decision-quality briefings.
- Ability to work in a hybrid NCR environment, report to the Pentagon or other Government facilities within required response times, and perform independently without routine Government or Contract PM assistance.
Preferred Qualifications- Graduate degree in data science, analytics, artificial intelligence, computer science, engineering, cybersecurity, information systems, operations research, or a related discipline.
- Prior experience supporting SAF/CN, Headquarters Air Force, a Service CIO/CDAO, DoW/DoD CIO, or an equivalent enterprise Data and AI governance organization.
- Project Management Professional (PMP), Certified Data Management Professional (CDMP), AWS or Azure data/cloud certification, security certification, or a recognized AI/ML credential.
- Experience with NIST AI RMF, AI system authorization, model risk management, MLOps, data catalogs, business-intelligence platforms, robotic process automation, and Government-approved generative-AI environments.
- Demonstrated experience producing measurable cycle-time, rework, cost, data-quality, risk-reduction, or decision-speed improvements through analytics, automation, or AI.
Performance Expectations- Own the technical quality, integration, security, and timely delivery of cross-program Data and AI products and maintain a Government-visible roadmap, use-case inventory, dependency register, and benefits tracker.
- Ensure every recommended or implemented AI use case includes documented mission value, authoritative data sources, data-readiness and risk assessment, responsible-AI controls, human-review requirements, evaluation criteria, and an accountable Government decision owner.
- Maintain at least 95% accuracy and timeliness for analytics, dashboards, automation products, and decision support, correcting identified quality issues promptly and documenting material data limitations.
- Prevent the introduction of Government data into unapproved AI services or tools and ensure analytics and AI artifacts remain auditable, transferable, and supportable without dependence on undocumented contractor knowledge.
- Quantify benefits from approved analytics, automation, and AI initiatives, including hours eliminated, cycle-time reduction, rework avoided, data-quality improvement, cost savings or avoidance, and mission-risk reduction.
- Provide the Program Manager and division leads with accurate status, risks, decisions, and upcoming milestones for program reporting and senior-leader review.
Benefits- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Family Leave (Maternity, Paternity)
- Short Term & Long Term Disability
- Training & Development
