2027 Internship – Data Science – System Performance Evaluation

Johns Hopkins Applied Physics Laboratory•Laurel, MD

4d•Onsite

About The Position

This internship focuses on leveraging computational and analytical skills to support multi-disciplinary teams in creating analysis and assessment approaches for defense and national security applications. The intern will contribute to advancing the state of the art in performance evaluation of strategic weapons systems throughout their lifecycle. The role involves working within a team of engineers, software developers, data scientists, and analysts in an environment that embraces innovation, integrity, trust, and teamwork.

Requirements

Pursuing a degree in Data Science, Statistics, Mathematics, Computer Science or related field
Experience with or knowledge of Python and/or R
Experience with developing extract, transfer, load processes for data quality pipelines, data science applications and dashboard tools, or statistical and machine learning methodologies for analysis
Able to obtain Interim Secret level security clearance by your start date and can ultimately obtain a final Secret level security clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
A minimum 3.0 GPA on a 4.0 scale.

Nice To Haves

Bachelor’s in Data Science, Statistics, Mathematics, Computer Science or related field
Experience with statistical analysis methodologies and design of experiments
Experience with or knowledge of SQL and Data Science frameworks (such as Tensorflow, Sci-kit learn, Numpy, PyTorch, Matplotlib, or more)

Responsibilities

Work with multi-disciplinary teams to develop data collection, processing, and analysis efforts to assess the performance of a number of systems supporting the Navy and Air Force.
Develop models and simulations to describe data, predict events, and prescribe a course of action that directly reflect stakeholder’s needs across a variety of domains.