The ideal candidate for this role brings strong analytical judgment, cognitive flexibility, hands-on comfort with data, and the ability to understand both the technical structure of data and the operational meaning behind it. Candidates for this role should be able to analyze, reason, and communicate well enough to contribute to analytics workflows, dashboard logic, data validation, and integration activities supporting the consolidated data environment that feeds the program’s agentic AI engine.
Experience with FAA, NAS, Aviation, air traffic operations, transportation, safety-critical systems, or large-scale modernization data is highly relevant to this position.
Key responsibilities may include, but are not limited to
Analyze workstream, requirements, IMS, schedule, risk, operational, and program data to identify trends, dependencies, gaps, anomalies, and decision-relevant insights
Define operational metrics, KPIs, analytical logic, thresholds, and decision-support views for Digital Command Center dashboards and advanced analytics products
Assess the quality, completeness, consistency, and usability of data made available through enterprise data repositories
Partner with data architects and data engineers to identify data gaps, transformation needs, metadata requirements, and analytics-readiness issues
Support ai-enabled analytics workflows by helping define trusted data inputs, context, validation criteria, and human-in-the-loop review considerations
Develop notebooks, scripts, SQL queries, statistical analyses, models, and reusable analytical artifacts to support data exploration and decision-making
Translate ambiguous operational questions into structured analysis, measurable metrics, and clear recommendations
Communicate assumptions, limitations, findings, and implications to technical teams, program leadership, and mission stakeholders
Qualifications
Required Qualifications
8+ years of experience with a BS/BA, 6+ years with a MS/MA, or 3+ with a PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, Operations Research, Information Systems, Analytics, or a related technical discipline
Experience analyzing complex structured, semi-structured, operational, program, or business datasets to support decision-making
Proficiency with Python, R, SQL, or similar analytical tools, with the ability to develop notebooks, scripts, queries, and reusable analysis artifacts
Experience with exploratory data analysis, data cleaning, statistical analysis, trend analysis, anomaly detection, forecasting, classification, clustering, or predictive modeling
Experience defining or supporting metrics, KPIs, dashboards, reports, or decision-support products
Ability to assess data quality, completeness, consistency, and analytical usefulness
Ability to translate ambiguous operational and stakeholder questions into structured analyses and measurable outputs
US Citizenship and the ability to obtain an FAA Public Trust clearance
Desired Additional Qualifications
Experience supporting FAA, aviation, NAS, air traffic management, transportation, defense, logistics, infrastructure, command center, risk, or other complex operational environments
Experience with cloud-based data environments, especially AWS, Glue, Athena, Redshift, SageMaker, Databricks, Snowflake, or similar
Experience working with data lakes, data warehouses, lakehouse environments, or multi-source data integration environments
Experience with dashboarding or visualization tools such as Tableau, Power BI, Grafana, Plotly, Dash, Streamlit, Superset, Qlik, or similar platforms
Familiarity with LLMs, agentic AI systems, retrieval-augmented generation (RAG), prompt/context engineering, AI-enabled workflows, or model/output evaluation
Experience supporting human-in-the-loop analytics, AI output validation, data quality frameworks, or decision-support governance
Experience working with requirements data, schedule data, risk data, dependency data, operational performance data, or program execution data
Familiarity with APIs, JSON, Parquet, data pipelines, ETL/ELT concepts, metadata, lineage, or data governance concepts
Experience contributing lightweight code to dashboards, data workflows, APIs, or analytics applications
Target Salary Range $104,000 - $166,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Benefits Statement
Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.
Application Statements The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. By applying to this job, you are expressing interest in the role and the Company. During the review of your application, you may be required to participate in an on-camera interview, as well as participate in a process to verify your identity. Use of artificial intelligence (AI) tools of any kind during Peraton interviews is strictly prohibited unless the candidate has obtained prior written authorization. All interview responses must be the candidate’s own.
- EEO
- EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.
