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Astronomy Data Scientist (Observatory) – Tucson, AZ

Lumenary Space Institute
Tucson, AZ
Salary Estimate
USD 90.000 – USD 120.000
Posting Time
8 Mei 2026
Deadline
8 Mei 2027

Job description

Join Lumenary Space Institute, a premier center for astronomical research and discovery. We are seeking a talented Astronomy Data Scientist to transform telescope and survey data into actionable insights that advance astrophysics and space exploration.

In this full-time role, you will collaborate with observatory teams, software engineers, and researchers to build scalable data pipelines, develop ML models for anomaly detection and classification, and deliver interactive tools that empower scientists and educators.

We value curiosity, rigorous methodology, and a passion for turning cosmic data into discoveries.

Responsibility

  • Architect and maintain end-to-end data pipelines for raw telescope and survey data, ensuring reproducibility and provenance.
  • Develop and deploy machine learning models for object detection, classification, time-series analysis, and anomaly detection.
  • Collaborate with astronomers to translate scientific questions into robust analysis workflows and experiments.
  • Build interactive dashboards and visualization tools to communicate findings to researchers and decision-makers.
  • Ensure data quality, lineage, versioning, and documentation; implement unit tests and CI/CD for data products.
  • Evaluate new algorithms, libraries, and cloud-based services to improve performance and scalability.
  • Prepare and present results for conferences, journals, and internal reviews.

Qualification

  • PhD in Astronomy, Astrophysics, Computer Science, or a closely related field; or MS with extensive research experience.
  • 3+ years of hands-on experience in astronomical data analysis and scientific computing.
  • Proficiency in Python (numpy, scipy, astropy) and SQL; experience with data visualization tools.
  • Experience with big data platforms and cloud services (AWS, GCP, or Azure).
  • Strong knowledge of ML/AI frameworks (scikit-learn, TensorFlow, PyTorch) and scientific computing workflows.
  • Familiarity with version control (Git) and reproducible research practices (notebooks, containers).
  • Excellent collaboration, communication, and scientific writing skills; ability to explain complex concepts to diverse audiences.
  • Track record of contributing to research papers or technical reports is a plus.

Required Skills

Python R SQL data analysis machine learning astrophysics astropy telescope data big data Docker Git data visualization

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