Data Scientist with Security Clearance
Redhorse Corporation · Tampa, FL · 2 wk ago
Information TechnologyFull-time
About the role
Redhorse transforms the way government uses data and technology. To support this mission, we are seeking a Senior Data Scientist to support the United States Central Command (USCENTCOM) Directorate of Logistics (CCJ4) at MacDill AFB.
Responsibilities
- Communicate regularly with client leadership regarding enterprise values, project direction, and mission objectives.
- Identify the intersection between strategic business value, simulation-based forecasting, and achievable technical work within the logistics domain.
- Articulate and translate complex business questions into technical solutions using available DoD data sources and mission-level modeling outputs.
- Explore and analyze diverse datasets—including live telemetry and simulated environments—to identify meaningful entities, relationships, and trends.
- Design and implement robust data ingestion and cleaning pipelines to ensure high-quality inputs for AI/ML models and stochastic simulations.
- Develop applications, simulation dashboards, and effective data visualizations to communicate complex insights and scenario outcomes to non-technical stakeholders.
- Serve as a technical ambassador for executive DoD leadership to sponsor and grow data literacy and modeling proficiency across the enterprise.
Requirements
- An active Secret security clearance is required (TS/SCI eligibility preferred).
- 8+ years of professional experience in data science, analytics, or Operations Research.
- Master’s degree from an accredited college or university in a quantitative discipline (Statistics, Computer Science, Physics, Electrical Engineering, or related STEM field).
- Proficiency in functional programming languages such as Python, R, or Scala.
- Strong experience with Modeling & Simulation (M&S) frameworks (e.g., AFSIM, EADSIM, STORM, or similar mission-level tools).
- Strong experience with database languages, specifically SQL.
- Demonstrated ability to discern and apply appropriate statistical and probabilistic modeling.