2026 PhD Graduate - Statistics and Data Science

Johns Hopkins Applied Physics Laboratory•Laurel, MD

20h•Onsite

About The Position

This position is for a new PhD graduate with expertise in statistics to support multi-disciplinary teams performing a variety of quantitative tasks for defense and national security applications. The role involves working with diverse teams of engineers, software developers, statisticians, data scientists, and analysts to advance the state-of-the-art in performance evaluation of strategic weapons systems. The work environment embraces innovation, integrity, trust, and teamwork, with a focus on continuous growth and learning.

Requirements

PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or a related field.
Strong interpersonal skills and the ability to work independently and on a team.
Strong foundations in statistical inference, probability, statistical modeling, and experimental design.
Experience using scientific programming tools such as Python, R, or similar languages for quantitative analysis.
Experience investigating and adapting modern statistical and computational methods to address emerging analysis challenges in sparse, noisy, or high-dimensional data settings.
Demonstrate experience with statistical modeling, inference, or experimental design approaches such as Bayesian methods, regression, causal inference, or hypothesis testing.
Able to obtain Interim Secret level security clearance by your start date and can ultimately obtain Top Secret level clearance.
U.S. citizenship.

Nice To Haves

Experience in project management or leading technical teams.
Experience in writing technical proposals, particularly to government research projects.
Experience mentoring students, teaching, or communicating complex technical concepts in academic, research, or professional settings.
Contributed to peer-reviewed publications, technical reports, or presentations in statistics, machine learning, applied mathematics, or related fields.
Experience using probabilistic programming frameworks such as Stan, PyMC, or similar tools.
Research or professional experience developing reproducible analytical workflows, computational research tools, or statistical methodologies for complex quantitative problems.

Responsibilities

Work with multi-disciplinary teams to support development of data collection, processing, and analysis efforts to assess the performance of a number of systems supporting the Navy and Air Force.
Develop and evaluate statistical models for complex defense applications, including uncertainty quantification, inference, forecasting, and decision support.
Apply statistical reasoning for data-driven studies, selecting appropriate methods (e.g., Bayesian or frequentist approaches) based on the problem.
Quantify and communicate uncertainty, assumptions, and limitations to support sound decision-making in complex, real-world settings.
Use internal funding opportunities to shape the direction of future research.
Communicate technical knowledge by articulating ideas clearly through papers and presentations to technical staff, management, and government decision makers.