Senior Data Scientist - Fort Bragg, NC

F3EA Inc•NC - Fort Bragg, Fort Bragg, NC, US, NC
•Onsite

About The Position

The Senior Data Scientist develops and applies advanced analytics to evaluate POTFF programs, identify readiness and human-performance trends, and support decision-making across the Special Operations enterprise. The role partners with domain experts and leaders to improve data collection, build reproducible analytical products, and translate complex findings into clear, actionable recommendations. This position is contingent upon F3EA receiving contract award and Government approval. Employment will not begin unless and until the position is funded and authorized.

Requirements

  • Bachelor's degree in data science, statistics, mathematics, computer science, operations research, engineering, public health, or a related quantitative field.
  • At least seven years of relevant analytics experience with a bachelor's degree, or five years with a relevant master's degree.
  • Advanced proficiency with Python or R, SQL, statistical modeling, data visualization, and reproducible analytical workflows.
  • Demonstrated experience developing and validating predictive models, communicating uncertainty, and translating findings for nontechnical decision-makers.
  • Experience working with sensitive, health, personnel, readiness, or operational data in a governed environment.
  • Ability to obtain and maintain a Secret or Top-Secret security clearance, depending on the position.
  • U.S. citizenship is required.

Nice To Haves

  • Graduate degree in a relevant quantitative discipline.
  • Experience supporting DoD, USSOCOM, Special Operations, human performance, public health, or program evaluation missions.
  • Experience with Power BI or Tableau, cloud analytics platforms, Git, MLOps practices, and secure data environments.
  • Knowledge of research design, longitudinal analysis, survey methods, and human-subjects or health-data protections.

Responsibilities

  • Design analytical approaches, data strategies, and measures of effectiveness for POTFF programs and initiatives.
  • Acquire, clean, integrate, validate, and document structured and unstructured data from multiple authorized sources.
  • Develop statistical, predictive, and machine-learning models to identify trends, risks, relationships, and program outcomes.
  • Build and maintain reproducible analyses, dashboards, visualizations, and decision-support products for technical and executive audiences.
  • Partner with POTFF domain professionals to improve data capture, define meaningful metrics, and evaluate program effectiveness.
  • Apply data-governance, privacy, security, quality-control, and version-control practices throughout the analytics lifecycle.
  • Present findings, limitations, and recommendations through clear briefings, technical reports, and written products.
  • Mentor analysts and contribute to analytic standards, peer review, and continuous improvement.
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