P

Peraton

Runs and secures technology for federal agencies

AI/ML Decision Intelligence Lead

Data ScienceConfirmed live in the last 24 hours
Full-timeHerndon, VA, USAIn-person

About the Job

Requirements

  • At least 12 years of experience with a BS/BA, 10 years with an 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.
  • 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 heterogeneous datasets.
  • Experience applying machine learning or modern AI methods to real-world problems, balancing 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.
  • 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.
  • 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.
  • U.S. citizenship and ability to obtain or maintain an FAA Public Trust.

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 heterogeneous 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.

Desired Qualifications

  • 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 lifecycle 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.

About the Company

Peraton

Runs and secures technology for federal agencies

Peraton builds and runs secure technology for American defense, intelligence, space, and civilian agencies, from military networks to satellite ground stations. In 2025, the Federal Aviation Administration chose it to manage the overhaul of the nation's air traffic control system, replacing copper wiring with fiber and upgrading radar and radios. Its engineers, many holding security clearances, run and defend agency networks and data centers, write mission software, and operate space and communications systems, and agencies pay for this work through multiyear contracts. Peraton was formed in 2017, when private-equity firm Veritas Capital bought Harris Corporation's government IT business, and is based in Reston, Virginia.

Company size
10,001+
Company stage
Grant
Total funding
$60M
Headquarters
Reston, VA
Founded
2017

Recently Posted Jobs

Explore more opportunities at Peraton

See more jobs