Senior Principal Data Scientist

YOUR IMPACT

Own your opportunity to work with the largest government agency in the nation. Make an impact by advancing the Department of War's mission to keep our country safe and secure.

IronEagleX (IEX), a wholly owned subsidiary of General Dynamics Information Technology (GDIT), delivers agile IT and Intelligence solutions. Combining small-team flexibility with global scale, IEX leverages emerging technologies to provide innovative, user-focused solutions that empower organizations and end users to operate smarter, faster, and more securely in dynamic environments.

IronEagleX is seeking a Senior Principal Data Scientist to join our dynamic team in Crystal City, VA. This role creates and delivers innovative analytic solutions as a member of a fast-paced, multidisciplinary team.

You will work directly with large, complex, and disparate datasets to develop practical analytic methods, identify meaningful patterns and relationships, and translate technical findings into capabilities and insights that support critical customer requirements.

As a Senior Principal Data Scientist, you will quickly turn large and complex datasets into clear, actionable insights for critical customer requirements. You will work closely with analysts, software developers, and other technical specialists to solve difficult data problems, develop new analytic approaches, and transition successful methods from exploratory analysis into repeatable and operational capabilities.

• Implement structured, repeatable data analysis across large, disparate datasets to surface patterns, trends, anomalies, relationships, and other signals in support of mission and analytic needs.

• Explore and characterize unfamiliar datasets, including assessing data quality, completeness, distributions, relationships, and limitations to determine appropriate analytic approaches and identify potentially useful signals.

• Develop, maintain, and improve analytic tooling such as queries, scripts, notebooks, lightweight services, and reusable code components to automate recurring workflows and enable rapid analysis.

• Develop and evaluate applied statistical, machine learning, and algorithmic approaches for problems such as classification, clustering, anomaly detection, similarity analysis, prioritization, entity resolution, relationship discovery, and predictive analysis.

• Establish appropriate validation methods, benchmarks, scoring approaches, thresholds, and measures of confidence to evaluate analytic performance and clearly communicate the strengths and limitations of analytic results.

• Build and enhance interactive analytic dashboards and lightweight GUIs, such as Streamlit applications, that support data exploration, linkage review, analyst workflows, model or algorithm evaluation, and generation of structured outputs.

• Create analyst‑ready products, including tables, visualizations, summaries, briefings, and structured exports, that translate technical findings into clear, decision-oriented insights.

• Work with analysts, engineers, and technical staff to convert ad hoc analyses and successful prototypes into reusable pipelines, standardized methodologies, documented workflows, and maintainable analytic capabilities.

• Support the integration, testing, and refinement of analytic methods in operational environments, ensuring outputs are reproducible, explainable, and usable by both technical and non-technical stakeholders.

• Document analytic assumptions, methodologies, data transformations, validation approaches, and known limitations to promote reproducibility, peer review, and continued improvement of analytic capabilities.

• Strong Python skills for building practical analytic…