Strategic Analytics & Modeling Intern

Systems Planning & Analysis; Alexandria (VA); On-site; USD 32,000 - 45,000; Full time

Job summary

Systems Planning and Analysis, Inc. (SPA) seeks a skilled analyst to provide objective, timely support to SSAG customers.

You will work collaboratively to formulate problems, propose methods, and conduct rigorous analysis for decision support in high-stakes environments. Ideal candidates combine optimization, data science, or physics-based modeling with programming in Python or R and a willingness to learn new approaches.

Qualifications

• US citizenship and the ability to obtain and maintain a DoD Top Secret Clearance.
• Pursuing a Bachelor’s or Master’s degree in Mathematics, Operations Research, Data Science, Computer Science, Physics, or a related technical discipline.
• Coursework or experience with linear optimization, discrete optimization, machine learning, Bayesian statistics, probability theory, or simulation.
• Experience with Python, R, or a similar programming language.
• Ability to report to designated work location in Alexandria, VA, up to full time, based on customer needs.

Responsibilities

• Develop and apply operations research techniques such as mathematical optimization, simulation, decision analysis, and statistical analysis.
• Decompose complex issues into simplified statements and clearly connect analysis to specific aspects of the problem.
• Develop and maintain tools and models to support analytic projects and processes.
• Create data visualizations to support decision analysis, model verification, and client communication.
• Assist in the development of briefings, memos, and other contract deliverables.

Skills

Python

R

Machine learning

Optimization

Statistics

Education

Bachelor's/Master's in Mathematics/OR/Data Science/CS/Physics

Tools

Tableau

Power BI

Job description

Systems Planning and Analysis, Inc. (SPA) seeks a skilled analyst to provide objective, timely support to SSAG customers.

You will work collaboratively to formulate problems, propose methods, and conduct rigorous analysis for decision support in high-stakes environments. Ideal candidates combine optimization, data science, or physics-based modeling with programming in Python or R and a willingness to learn new approaches.