ENERGY AND WATER Statistician Security Clearance

Position: ENERGY AND WATER STATISTICIAN with Security Clearance
ENERGY AND WATER STATISTICIAN
Concurrent Technologies Corporation
Crystal City, VA Minimum

Clearance Required:

N/A
Clearance Level Must Be Able to Obtain:
Secret
Employee Background Check Required As a trusted partner and leader in providing energy and sustainability consulting services to the federal government, Concurrent Technologies Corporation (CTC) understands the increasing complexity of achieving energy security and data management in a changing world. As part of the Energy, Resilience and Sustainability (ERS) Division, you will collaborate with experts to provide comprehensive policy, planning, and implementation services to deliver solutions that address critical infrastructure resilience and security, and data management issues and support the military mission, while reducing environmental impacts.

We take our role seriously, as our efforts ensure our installations and assets are prepared in any operating environment, present and future. CTC is seeking a highly motivated and qualified statistician with experience in energy and water resources and data center infrastructure planning. This mid-career role offers the opportunity to unify disparate water, energy, environmental, and mission support information into a single, structured analytical model designed specifically for data center siting.

The position blends hands-on technical analysis, risk assessment, and client-facing activities. In this role, you will focus on developing a scalable, statistically driven risk assessment framework that prioritizes water and energy resource impact assessment and installation risk tolerance assessments to support the Department of the Air Force (DAF) in resilient data center siting. This is a hybrid position located in the Washington, D.C. area, with the flexibility to work from home while participating in some in-person client and team discussions at or near our Crystal City office.

Candidates must be in the Washington, DC area or willing to relocate. Recurring in-office work may be required (e.g., every Monday) at client direction. This role provides a unique opportunity to develop expertise at the intersection of water and energy system operations, facility resilience, and mission assurance—key areas for ensuring the security and sustainability of government and defense infrastructure.

Key Responsibilities:

• Statistical Model Development:
Develop and apply statistically rigorous models to assess water and energy risks, define analytical parameters, and generate defensible, data-driven insights for data center prioritization at DAF installations.

• Data Transformation & Analysis:
Translate raw datasets (internal and external) into standardized, machine-readable parameters suitable for statistical modeling. Develop and document data transformation processes and analytical functions.

• Risk Assessment:
Analyze technical utility frameworks, energy and water supply technology capabilities, and data center requirements. Quantify installation-specific risks and resilience metrics.

• Tool Integration & Verification:
Integrate statistical models into the project’s assessment tool. Conduct iterative testing and verification to ensure accuracy, repeatability, and defensibility of outputs.

• Stakeholder Engagement:
Collaborate with project leads, data engineers, research analysts, and government stakeholders to define model requirements, validate assumptions, and refine analytical approaches.

• Documentation & Reporting:
Prepare technical documentation, user guidance, and verification reports for model parameters, transformation logic, and tool outputs.

Basic Qualifications:

• Master’s degree or higher in Statistics, Applied Mathematics, Data Science, or a related quantitative field.

• Minimum six (6) years of professional experience in statistical analysis, predictive modeling, or quantitative research

• Demonstrated experience in statistical analysis, predictive modeling, and hypothesis testing.

• Proficiency in statistical programming languages (e.g., R, Python, SAS) and data visualization tools.

• Experience translating complex quantitative results into actionable recommendations for technical and non-technical…