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Senior Astronomical Data Scientist

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Job Description - Senior Astronomical Data Scientist

Job Summary

This role supports NASA flagship space science missions by advancing astronomical data analysis and visualization tools used by the global research community. The position combines product ownership responsibilities with hands-on scientific software development, focusing on Python-based analysis tools and Jupyter notebook environments designed for complex astronomical datasets.

The primary responsibility is serving as a Product Owner for a Scrum team developing data analysis tools and notebooks for astronomers. This includes setting priorities, defining product vision and goals, translating scientific requirements into technical specifications, and acting as the main liaison between stakeholders and the development team. The role also involves active engagement with the astronomy community to gather feedback and promote tool adoption through outreach, conferences, and meetings.

In addition, the position contributes directly to software and algorithm development, user support, training, and improvements to software engineering processes. Work includes developing advanced data visualization solutions, contributing to open-source scientific Python packages, and building scalable cloud-accessible Jupyter notebook workflows. Development efforts may span image processing, spectroscopy, photometry, astrometry, signal processing, modeling, statistics, and numerical simulations.

Key Responsibilities

  • Drive product success through close collaboration with software developers

  • Translate scientific and mission needs into clear product and technical requirements

  • Serve as the primary point of contact between stakeholders and the development team

  • Prioritize, maintain, and manage the product backlog

  • Promote data analysis tools through community engagement and outreach

  • Design, develop, test, and deploy Python-based scientific software

  • Develop and maintain Jupyter notebooks focused on real-world scientific use cases

Qualifications

  • Experience working with astronomical data and understanding user needs from a data pipeline and analysis perspective

  • Experience with space-based observatory data is a plus

  • Strong Python skills, including performance optimization for large datasets

  • Experience with unit testing and test-driven development practices

Education

  • Bachelors degree in Astronomy, Physics, or a related field

  • Advanced degree preferred, with 8+ years of experience in astronomical research or observatory science support

  • Background in astronomy or scientific software development within a research environment is highly valued

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