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Senior Data Scientist

Johns Hopkins Applied Physics Laboratory (APL)Laurel, Maryland🇺🇸United StatesPosted 5 Sept 2026

Why This Role Stands Out

Advance your career with Johns Hopkins APL by developing cutting-edge AI solutions for critical national security and space missions, enjoying a hybrid work environment that fosters collaboration and learning. You'll thrive here if you're passionate about leading complex data science projects, mentoring others, and pushing the boundaries of machine learning in a research-driven, impactful setting. This role offers exceptional opportunities for professional growth and the chance to contribute to groundbreaking work.

Quick Overview

Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
Laurel, Maryland, United States
ETLMLOpsMachine LearningScikit-learnComputer VisionDeep LearningPandasPython

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

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