Data Scientist

Johns Hopkins Applied Physics Laboratory (APL) seeks a Data Scientist to apply advanced analytics, machine learning, and statistical modeling to national security, space, and health challenges. In this role, you will design and implement data-driven solutions, build scalable data pipelines, and collaborate with multidisciplinary experts to turn complex data into mission impact. You will explore cutting-edge techniques, communicate insights to diverse stakeholders, and contribute to research, publications, and prototype systems in a highly collaborative, mission-driven environment that supports continuous learning and innovation.

Responsibilities

• Design and implement machine learning and statistical models to solve complex national security, space, and health problems.
• Collect, clean, integrate, and analyze large, heterogeneous datasets from multiple sources.
• Develop production-quality data pipelines, analytical tools, and reusable model components.
• Collaborate with scientists, engineers, and domain experts to translate mission needs into analytical approaches.
• Visualize and communicate findings, methods, and assumptions to technical and non-technical stakeholders.
• Document methodologies, experiments, and results; contribute to technical reports and publications.
• Evaluate and compare modeling approaches; perform rigorous testing, validation, and performance tuning.
• Stay current with emerging data science methods, tools, and best practices and apply them to APL missions.

Required Skills

• Machine learning (supervised and unsupervised methods)
• Statistical analysis and modeling
• Python programming (Num
• Py, pandas, scikit-learn, etc.)
• Deep learning frameworks (Tensor
• Flow or Py
• Torch)
• Data wrangling and ETL pipeline development
• SQL and No
• SQL databases
• Data visualization (e.g., Matplotlib, Plotly, Tableau)
• Cloud platforms (AWS, Azure, or GCP)
• MLOps and model deployment practices
• Version control and collaborative development (Git)