2027 Graduate - Data Scientist; Computer Scientist; Engineer - Decision Systems

Join the Decision Systems Group at Johns Hopkins Applied Physics Laboratory (APL) to build decision support systems and data-driven, explainable solutions as a 2027 Graduate in an interdisciplinary environment.

Responsibilities

• Support a team designing and developing high-performance, scalable, and resilient decision support systems
• Collaborate with internal and external partners to translate system concepts into clear plans of action
• Build proof of concept prototypes to evaluate new technologies aligned to sponsor missions
• Conduct research and analysis to shift approaches from reactive to proactive

Requirements

• Earned a Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Electrical Engineering, or a similar field
• Proficient in at least one programming language commonly used in data science and/or full-stack development, such as Python, Java, or JavaScript
• Outstanding written and oral communication skills
• Organizational skills and a strong relationship-building mindset
• Ability to acquire an Interim Secret security clearance by the start date, and ultimately obtain a final Secret clearance
• Subject to a government security clearance investigation if selected; eligibility requirements include U.S. citizenship

Technologies

• Python
• Java
• JavaScript

Compensation

• Minimum: $85,000 annually
• Maximum: $165,000 annually

Education

• Bachelor’s or Master’s degree

Location

• Laurel, MD (onsite)

Benefits

• Robust education assistance program
• Unparalleled retirement contributions
• Healthy work/life balance
• Comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability
• Flexible spending accounts
• Education assistance
• Training and development

Preferred (Above and Beyond)

• Prior experience as a researcher or practitioner in one or more areas: Generative AI, Deep Learning, Optimization, Natural Language Processing, Operations Research, Supply Chain Analysis, Software Engineering, Data Visualization, Data Engineering, DevOps/MLOps, Public Health Surveillance, Health Informatics
• Demonstrated ability to communicate analyses of real-world data sets to audiences with broadly varying technical backgrounds