Job description
Join Lumen Observatory and Research Institute, a leading center for astronomical discovery and public science outreach. We are seeking a talented Astronomy Data Scientist to transform raw telescope data into accessible insights and high-impact research outputs. The successful candidate will blend domain knowledge with modern data engineering and ML to accelerate discovery and inspire the next generation of astronomers.
This role offers a unique opportunity to work with world-class facilities in Flagstaff, collaborate with international teams, and contribute to open data initiatives. We value curiosity, rigor, and clear communication.
Responsibility
- Lead the analysis of astronomical survey data, including photometry, astrometry, and spectral data.
- Develop scalable data pipelines and dashboards to support telescope scheduling and data quality monitoring.
- Collaborate with astronomers to design experiments and interpret results for publications.
- Implement machine learning methods for anomaly detection, event classification, and image processing.
- Maintain and extend data catalogues, metadata standards, and data provenance records.
- Prepare researchers and students to use data through tutorials, documentation, and outreach materials.
- Participate in instrument commissioning, calibration, and software integration for observatory systems.
- Represent the institute at conferences and collaborate with partner universities on joint projects.
Qualification
- Master’s degree or PhD in Astronomy, Astrophysics, Computer Science, or a related field.
- Strong programming skills in Python and proficiency with scientific libraries (NumPy, SciPy, Astropy).
- Experience with SQL/NoSQL databases, data warehousing, and ETL processes.
- Hands-on experience with astronomical data formats (FITS, VOTable) and photometric/astrometric pipelines.
- Familiarity with Linux/Unix environments, version control (Git), and containerization (Docker).
- Experience with machine learning methods for image analysis and time-series data.
- Excellent communication skills and ability to work effectively in cross-disciplinary teams.
- Demonstrated ability to manage multiple projects with attention to detail and deadlines.