AI / Data Analyst

Peraton•Herndon, VA

7d•$135,000 - $216,000•Onsite

About The Position

Peraton is seeking an AI / Data Analyst to support the development and application of AI-enabled solutions in a mission-focused environment under the FAA’s Brand-New Air Traffic Control System (BNATCS) contract. The role applies analytical expertise to Generative AI and advanced data analytics, including modern Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), and cloud-based AI technologies. The analyst will help move AI capabilities from concept to production by developing secure and responsible solutions that let users interact with complex information more quickly and intuitively. The position is intended for experienced analytical professionals and does not require a traditional software-engineering career path. The analyst works with diverse data sources, identifies patterns and relationships, evaluates information, and translates complex data into useful insights. They collaborate with AI engineers, data scientists, software developers, and mission stakeholders to develop AI-enabled capabilities for the FAA’s air traffic management mission. The position is 100% on-site in Herndon, Virginia.

Requirements

U.S. citizenship.
Ability to obtain and maintain a Public Trust clearance.
One of the following education and experience combinations: bachelor’s degree and 12 years of experience; master’s degree and 10 years; associate’s degree and 14 years; or high school diploma/equivalent and 16 years.
Background as an Intelligence Analyst, All-Source Analyst, Data Analyst, Research Analyst, Business Intelligence Analyst, or similar analytical professional.
Experience integrating, manipulating, or analyzing information from multiple disparate data sources.
Experience working with large volumes of structured and unstructured data.
Familiarity with Generative AI, LLMs, NLP, or AI-assisted analytical tools.
Experience using LLM-based platforms such as ChatGPT, Claude, Gemini, or Microsoft Copilot for research, analysis, summarization, or information synthesis.
Experience developing prompts or applying prompt engineering and evaluating AI-generated responses.
Demonstrated experience working with and manipulating large, complex, or diverse datasets from multiple sources.
Experience validating data quality and identifying incomplete, inconsistent, or conflicting information.

Nice To Haves

Experience supporting federal government, defense, intelligence, aviation, or other mission-critical environments.
Proficiency with common data analysis and productivity tools such as Microsoft Excel and related reporting or visualization applications.
Understanding of data governance, information security, privacy, and Responsible AI principles.
Professional experience in intelligence analysis, all-source analysis, data analysis, research, business intelligence, operations analysis, or a related analytical discipline.
Experience with data visualization or business intelligence tools such as Power BI or Tableau.
Familiarity with SQL, Python, or other data manipulation or query tools; not required.
Experience analyzing structured and unstructured information to identify patterns, trends, relationships, anomalies, and actionable insights.
Demonstrated ability to research, evaluate, correlate, and synthesize information from multiple sources.

Responsibilities

Collect, organize, manipulate, and analyze structured and unstructured data from multiple sources.
Evaluate large and diverse datasets to identify patterns, trends, relationships, anomalies, and potential risks.
Apply analytical techniques to transform complex information into actionable insights and recommendations.
Support the use of Generative AI and LLMs to analyze, summarize, categorize, and extract insights from information.
Develop and refine prompts to improve the quality and accuracy of AI-generated results.
Evaluate AI-generated outputs for accuracy, relevance, completeness, and consistency.
Research and correlate information across multiple data sources to build a more complete understanding of complex issues.
Prepare data for AI-enabled analysis, including validating, cleansing, normalizing, tagging, and organizing it.
Support dashboards, reports, visualizations, and analytical products that communicate findings to stakeholders.
Work with AI engineers, data scientists, software developers, and mission stakeholders to translate analytical requirements into AI-enabled capabilities.
Identify opportunities for AI, automation, and advanced analytics to improve existing analytical processes.
Document analytical methodologies, data sources, assumptions, findings, and recommendations.
Apply appropriate data governance, security, privacy, and responsible AI practices when handling sensitive information.