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Astronomy Data Scientist

Celestial Analytics Lab
Pasadena
Salary Estimate
USD 120.000 – USD 190.000
Posting Time
5 Mei 2026
Deadline
5 Mei 2027

Job description

Join the Celestial Analytics Lab, a leading astronomy research group based in Pasadena, CA, solving the universe's mysteries through data. You will develop and optimize data pipelines that transform raw telescope feeds into clean, searchable datasets for research and visualization. Our team blends astronomy, software engineering, and data science to accelerate discoveries and public outreach.

You will work closely with astronomers, engineers, and educators to turn complex scientific questions into robust, repeatable analyses.

Responsibility

  • Develop and maintain scalable data processing pipelines for astronomical data from ground and space telescopes.
  • Collaborate with astronomers to translate scientific questions into data-centric experiments and analyses.
  • Build predictive models, anomaly detection, and quality controls for instrument and survey data.
  • Design and implement interactive dashboards and visualizations for researchers and stakeholders.
  • Optimize code for HPC clusters, cloud environments, and Linux-based workflows.
  • Document workflows, ensure data provenance, and promote reproducible research practices.

Qualification

  • M.S. or Ph.D. in astronomy, physics, data science, or a closely related field.
  • Strong Python experience with NumPy, SciPy, pandas, and Astropy; solid SQL skills.
  • Experience handling large astronomical datasets and telescope data; familiarity with data pipelines and metadata standards.
  • Applied machine learning experience to scientific problems; ability to translate results into actionable insights.
  • Experience with Linux, HPC/cloud computing, version control (Git), and collaborative software development.
  • Excellent communication skills and ability to work across cross-disciplinary teams.

Required Skills

Python Astropy SQL data processing machine learning data visualization Linux HPC cloud computing Git astronomy data

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