Job description
Lowell Observatory is seeking a results-driven Senior Astronomy Data Scientist to lead the development of advanced data analysis workflows for imaging and spectroscopic datasets. You will partner with astronomers and instrument teams to design, implement, and optimize scalable data pipelines, contribute to open science by sharing code and results, and mentor junior data scientists.
As a cornerstone of our research program, you will work with terabytes of observational data, apply machine learning methods to classify sources, detect transient events, and characterize celestial objects. This role offers the chance to impact cutting-edge astronomy while working in a collaborative, mission-driven environment.
Responsibility
- Build and maintain scalable data processing pipelines for telescope and survey data.
- Develop statistical and machine learning models for source classification, anomaly detection, and transient alert generation.
- Collaborate with astronomers to translate science goals into robust software and analyses.
- Optimize computational workflows for high-performance computing (HPC) environments and cloud resources.
- Contribute to open-source software and participate in publications and conference presentations.
- Mentor junior data scientists and provide code reviews to ensure high-quality deliverables.
- Ensure data quality, provenance, and reproducibility through governance, testing, and documentation.
Qualification
- PhD in Astronomy, Astrophysics, Computer Science, or a closely related field; or a Master's with strong research record.
- Strong programming experience in Python; proficiency with NumPy, SciPy, and data analysis libraries.
- Experience applying ML/AI methods to astronomical data (imaging, time-domain, or spectroscopy).
- Proficiency in SQL and data visualization tools; ability to communicate complex results to diverse audiences.
- Experience with HPC clusters and cloud platforms (AWS, GCP) for large-scale data processing.
- Excellent collaboration, communication, and mentoring skills; ability to work in cross-disciplinary teams.
- Demonstrated track record through publications, code repositories, or notable projects.