Senior Data Scientist

About Redhorse Corporation

Redhorse Corporation specializes in delivering data-driven insights and technology solutions to clients involved in critical missions for the U.S. government. The company values dedicated professionals who excel as collaborative partners and who build technology-independent solutions to support challenging and vital mission objectives.

Position Overview

We are seeking a Senior Data Scientist to contribute to the United States Central Command (USCENTCOM) Directorate of Logistics (CCJ4) at MacDill Air Force Base. This role entails playing an essential part in advancing AI-powered capabilities within the Joint Logistics Enterprise by integrating AI and machine learning features into many automated and manual Department of Defense (DoD) data streams. Your efforts will directly enhance planning speed and decision-making that support regional partnership and deterrence strategies throughout the USCENTCOM area.

Core Responsibilities

• Engage routinely with client leadership to discuss enterprise objectives, project strategies, and mission goals.
• Identify areas where strategic business value aligns with simulation forecasting and realistic technical capabilities in the logistics sector.
• Convert complex business challenges into technical solutions using diverse DoD data and mission-specific modeling results.
• Analyze varied datasets, including live telemetry and simulations, to uncover important entities, correlations, and trends.
• Design and maintain robust data integration and cleaning pipelines ensuring quality inputs for AI/ML models and stochastic simulations.
• Develop applications and dashboards that visualize simulations and data insights for communication to non-technical leadership.
• Act as a technical liaison to senior DoD leaders to enhance data literacy and modeling expertise across the organization.

Required Qualifications and Experience

• Active Secret security clearance is necessary; eligibility for TS/SCI clearance is preferred.
• At least eight years of professional background in data science, analytics, or operations research.
• Master’s degree in a quantitative STEM field such as Statistics, Computer Science, Physics, or Electrical Engineering from an accredited institution.
• Proficiency in functional programming languages like Python, R, or Scala.
• Extensive experience with Modeling & Simulation tools (e.g., AFSIM, EADSIM, STORM).
• Strong command of SQL and database query languages.
• Ability to select and apply appropriate statistical and probabilistic models based on mission context.
• Skilled in conveying findings through technical visualizations, briefings, and reports.
• Independent problem-solving capability alongside effective teamwork.
• Willingness to travel up to 10% as required.

Preferred Skills and Experience

• Doctorate degree in a quantitative discipline.
• Experience integrating simulation data into enterprise platforms such as Advana or MAVEN.
• Proficiency working on cloud platforms like AWS, Azure, or GovCloud.
• Experience with large-scale data processing and distributed computing frameworks like Spark or Databricks.
• Advanced capabilities using data visualization tools such as Tableau, PowerBI, or R/Shiny.
• Familiarity with DoD logistics data, USCENTCOM missions, and Joint Staff modeling needs.

Additional Information

The salary provided is a base expectation and will be adjusted depending on experience, qualifications, certifications, security clearance, and market factors. Employees may also have access to benefits programs and performance-based incentives.

Redhorse Corporation is committed to equal opportunity employment and non-discrimination based on protected classes. Reasonable accommodations are available for applicants with disabilities.

This job description may be modified at the company's discretion to meet evolving requirements.

Artificial intelligence tools may assist parts of the hiring process such as application review and resume analysis; however, final decisions are made by human recruiters. Questions about data processing may be directed to Talent Acquisition.