AI/ML Decision Intelligence Lead

Peraton•Bowie, MD

4d•$146,000 - $234,000

About The Position

Peraton Labs is seeking an AI/ML Decision Intelligence Lead to support the BNATCS CTO organization in developing advanced analytics, AI-enabled decision support, and agentic AI capabilities for one of the nation’s most significant aviation modernization efforts. The BNATCS CTO is building the analytical, data, and AI foundation needed to help program and government stakeholders understand complex program dynamics, identify emerging risks, evaluate tradeoffs, and make better-informed decisions across a large-scale aviation system-of-systems environment. This includes integrating and analyzing programmatic, engineering, operational, and workstream data; developing decision-grade analytical products and shaping how advanced AI and analytics are applied to support execution, modernization, and mission outcomes. This role will serve as a senior technical leader responsible for designing, developing, and guiding advanced analytics and AI capabilities that turn complex data into actionable insight. Candidates for this role should have deep hands-on technical depth, strong analytical judgment, comfort working across ambiguous data environments, and the ability to brief senior stakeholders with clarity, confidence, and credibility. The ideal candidate for this position is a technical leader who can bridge artificial intelligence, machine learning, operations research, statistical modeling, systems thinking, and mission-focused execution by helping define analytical approaches, lead complex technical development efforts, guide data fusion strategies, mentor technical contributors, and shape the BNATCS CTO roadmap for AI-enabled decision intelligence and agentic analytics.

Requirements

12+ years of experience with a BS/BA, 10+ years with a MS/MA, or 6+ years with a PhD in AI/ML, data science, computer science, artificial intelligence, aerospace, systems engineering, or a related technical field
Demonstrated experience developing or leading advanced analytics, AI/ML, predictive modeling, simulation, optimization, or decision-support capabilities in complex technical environments
Strong ability to transform large, complex, or ambiguous datasets into decision-ready insights for senior technical, operational, programmatic, or government stakeholders
Experience framing complex analytical problems, selecting appropriate methods, developing evaluation approaches, and communicating assumptions, limitations, confidence, and decision implications
Experience with multi-source data integration, data fusion, data quality, assessment, temporal alignment, entity resolution, or analytical preparation of heterogenous datasets
Experience applying machine learning or modern AI methods to real-world problems, with the judgment to balance model performance, interpretability, reliability, governance, and operational usefulness
Experience supporting mission-critical, safety-conscious, highly regulated, government, aviation, defense, transportation, infrastructure, or large-scale systems environments
Demonstrated ability to lead technical contributors, mentor analytical staff, review technical work, and guide multidisciplinary execution across AI/ML, analytics, data, and engineering teams
Familiarity with agentic AI, intelligent workflow automation, human-machine teaming, decision intelligence, or AI-enabled operational support systems
Experience with transformer-based models, natural language processing, retrieval augmented generation, knowledge graphs, GraphRAG, or semantic data integration
Strong executive communication skills, including the ability to brief senior leaders on complex analytical, technical, and strategic topics
Ability to work effectively with government stakeholders, technical teams, program leaders, and cross-functional partners in fast-moving and ambiguous environments
US Citizenship with the ability to obtain/maintain an FAA Public Trust

Nice To Haves

Experience with FAA, aviation, air traffic, airline operations, transportation systems, National Airspace System modernization, or other complex system-of-systems domains
Familiarity with MLOps, model monitoring, evaluation automation, reproducible pipelines, data lineage, model governance, and analytical lifestyle management
Experience creating executive dashboards, analytical decision-support tools, operational insight products, or visualization strategies for senior decision makers
Experience establishing analytical standards, governance practices, model evaluation frameworks, or responsible AI practices in high-governance environments

Responsibilities

Lead the design, development, and application of AI/ML, advanced analytics, and decision intelligence capabilities supporting BNATCS CTO priorities
Transform complex programmatic, engineering, operational, and aviation-domain data into actionable insight for leadership, technical teams, and government stakeholders
Develop analytical frameworks that support continuous monitoring, evaluation, and improvement of program performance, technical progress, operational readiness, and emerging risk areas
Design and guide predictive models that identify early indicators of risk across schedule, cost, technical integration, operational performance, data readiness, and mission execution
Apply machine learning, statistical modeling, operations research, simulation, optimization, and probabilistic methods to support scenario analysis, tradeoff evaluation, resource planning, and decision support
Lead data fusion strategies across heterogenous data sources, including multi-source correlation, entity resolution, temporal alignment, data quality evaluation, lineage, and analytical readiness
Identify, assess, and align data sources required to support advanced analytics, agentic AI workflows, visualization products, and decision-support capabilities
Develop strategies for working with sensitive, incomplete, inconsistent, or restricted data, including potential use of synthetic data generation, privacy-preserving methods, and representative test datasets
Evaluate opportunities to apply agentic AI, transformer-based methods, natural language processing, retrieval augmented generation, knowledge graphs, or other emerging AI techniques to mission relevant analytical workflows
Ensure analytical methods are interpretable, reliable, testable, reproducible, and appropriate for high-governance, safety-conscious, and mission-critical environments
Define evaluation approaches for AI/ML and analytical products, including performance measures, confidence communication, assumptions, limitations, validation methods, and operational suitability
Partner with data, architecture, engineering, visualization, and workstream stakeholders to translate operational needs into measurable analytical outputs and technical delivery plans
Create executive-ready briefings, analytical products, technical roadmaps, decision-support artifacts, and recommendations that communicate complex findings clearly to senior stakeholders
Brief FAA, BNATCS, and internal leadership on analytical products, model results, decision implications, technical risks, capability gaps, and recommended paths forward
Establish best practices for decision intelligence, model governance, reproducible analysis, documentation, data-driven program insight, and responsible AI use within the BNATCS environment
Identify analytical risks early, including data quality concerns, weak assumptions, model drift, insufficient validation, governance gaps, or operational adoption barriers, and recommend mitigation strategies