Senior Data Scientist

  • Johns Hopkins Applied Physics Laboratory (APL)
  • Laurel, Maryland
  • 09/12/2026
Full time Information Technology Telecommunications

Job Description

Senior Data Scientist - Defense & Aerospace Johns Hopkins Applied Physics Laboratory (APL) seeks a Senior Data Scientist to develop advanced analytics and AI solutions for national security and space missions. You will design and deploy machine learning and statistical models, lead end-to-end data science projects, and collaborate with domain experts to deliver decision-quality insights. In APL's mission-driven, research-focused culture, you'll explore cutting-edge methods, publish and prototype, mentor junior staff, and help shape ethical, high-impact AI systems that address critical national and global challenges.

Responsibilities

  • Design, implement, and validate advanced machine learning and statistical models for defense and aerospace applications
  • Lead end-to-end data science projects from problem framing through deployment and transition to sponsors
  • Collaborate with engineers, analysts, and mission experts to translate complex operational needs into analytic solutions
  • Mentor and guide junior data scientists, promoting best practices in coding, modeling, and documentation
  • Prototype, evaluate, and communicate novel AI approaches through reports, briefings, and, when appropriate, publications
  • Ensure models are robust, explainable, and aligned with ethical and responsible AI principles
  • Work with software and systems engineers to operationalize models in real-world environments
  • Engage with sponsors to define requirements, present results, and shape future research directions

Required Skills

  • Machine learning (supervised, unsupervised, and deep learning)
  • Statistical modeling and inference
  • Python programming (Num
  • Py, pandas, scikit-learn, Py
  • Torch/Tensor
  • Flow)
  • Data engineering and ETL for analytics
  • MLOps and model deployment (CI/CD, containers, cloud)
  • Bayesian methods and probabilistic modeling
  • Experiment design and A/B testing
  • Natural language processing or computer vision (preferred)
  • Big data tools (Spark, distributed computing)
  • Domain knowledge in defense, aerospace, or national security analytics