DM Science Validation Scientist

Submission Information
Publish Date: 
Tuesday, March 5, 2019
Archive Date: 
Tuesday, April 2, 2019
Job Summary
Job Category: 
Scientific/Technical Staff
Institution Classification/Type: 
Street Line 1: 
950 N. Cherry Avenue
United States of America
Job Announcement Text: 

The Association of Universities for Research in Astronomy, Inc. (AURA) operates several observatory centers (including the National Optical Astronomy Observatory, the National Solar Observatory and the Gemini Observatory) in the United States and Chile under cooperative agreements with the National Science Foundation (NSF). AURA also has cooperative agreements with the NSF to construct the Daniel K. Inouye Solar Telescope (DKIST) and the Large Synoptic Survey Telescope (LSST).

LSST, now under construction, will be large-aperture, wide-field, ground-based telescope-camera-data processing system that will digitally survey half the sky every few nights in six optical bands. It will explore a wide range of astrophysical questions, ranging from discovering “killer” asteroids, exploring the time domain universe, mapping the evolution and structure of our Milky Way galaxy, to examining the nature of dark matter and dark energy. The project includes an 8-meter class wide field telescope, a 3.2 gigapixel camera with 2-second readout, and a state-of-the-art peta-scale data management system to process, archive, and distribute the 15 TB of data produced every night. LSST Construction started an 8-year effort in July 2014. LSST is a single project funded by both the National Science Foundation and Department of Energy. Once completed, the LSST will be the largest and most modern optical survey project ever built and a flagship of US science and engineering. The LSST Data Management (DM) system is being constructed by a team of 100+ members residing at partner institutions across the United States and Chile. It includes a data processing system spanning two continents, new state-of-the-art image processing algorithms, peta-scale computing clusters with tens of thousands of cores, large distributed databases, and next-generation analysis toolkits, among others. All LSST DM code is free software (GPL v3), written in modern Python and C++.

LSST is soliciting applications for a DM Science Validation Scientist within the DM Subsystem Science Team (DM-SST) based out of the LSST Project Office (Headquarters) in Tucson, AZ. The DM Science Validation Scientist leads the scientific validation of the DM Subsystem and Data Products. Science Validation is the process by which we assess that the as-built Data Management system meets the needs of the scientific community and other identified stakeholders, thus enabling the community to deliver the discoveries that LSST data promise. The DM Science Validation Scientist is responsible for the organization and coordination of all science validation activities across DM, including large-scale data challenges, and is responsible for end-to-end science validation. S/he coordinates the design, development and execution of test specifications and acceptance test plans to demonstrate that the LSST DM System has met its design requirements.

The DM Science Validation Scientist reports to the DM Subsystem Scientist and is a full member of the DM Subsystem Science Team. We are looking for a scientist with a broad interest and experience in astronomical surveys, algorithms and software to ensure that DM deliverables are built to specification, and to scientifically validate their readiness for commissioning and operations. Twenty percent of your time will be available for personally-directed research. The position being sought runs through the completion of the LSST Construction Project (c. late 2022) with multiple opportunities for continued engagement during the LSST’s operational phase.


Essential Functions:

  • Validate the science quality of DM deliverables and the capability of all elements of the DM System to achieve LSST science goals.
  • Develop detailed validation test plans for the LSST Data Management System.
  • Generate test cases & specifications to verify the LSST Data Management System requirements.
  • Convert test specifications into executable code (e.g. Python) within the test and metric verification framework.
  • Execute test plans, analyze results against science requirements, troubleshoot problems, and identify areas for improvement.
  • Identify additional expertise from the wider LSST Construction Project or Science Collaborations to assist with highly domain-specific validation activities, where necessary.
  • Deliver reports on the assessed state and capabilities of the DM system, and develop responses to non-compliances.
  • Contribute to and monitor the evolution of the DM system requirements.
  • Measure performance metrics, both automated and manual, and identify new metrics to characterize system performance.
  • Facilitate the implementation of approved change and deviation requests.
  • Work with the LSST commissioning and Systems Engineering teams to implement best practices, and maximize shared resources, test plans, software and tools where possible.
  • Support the LSST commissioning team in understanding the outputs of the DM system.

Minimum Requirements:

  • Ph.D. in Astronomy, Physics or related.
  • Demonstrated knowledge of astronomical image processing and analysis techniques.
  • Experience with the verification and validation of astronomical algorithms and pipelines.
  • At least two years’ proven experience programming scientific software using Python.
  • Demonstrated knowledge of software management and version control.
  • Demonstrated knowledge of UNIX/Linux based systems.
  • Ability to work effectively with minimal direction, to document and give direction to others.
  • Ability to speak and write effectively, including preparation and presentation of reports.
  • Attention to detail and commitment to achieving high quality results on time.
  • Ability to cooperate with and obtain the support of others.

Desired Experience/Skills/Abilities:

  • Experience with the LSST science pipelines and the LSST Science Platform is an advantage.
  • Demonstrated knowledge of Python's open data science stack, including NumPy, SciPy, Pandas, Matplotlib, Scikit-learn, iPython and Jupyter-Lab.
  • Experience with the analysis and visualization of large datasets using Python and high-level tools, such as PyViz, Bokeh, Datashader, Dask, Spark.
  • Knowledge of SQL or similar language for database interaction. 
  • Understanding of software engineering, agile processes and test driven design.
  • Troubleshooting skills and ability to learn new technologies.
  • Experience working in large geographically distributed scientific projects.
  • Experience with large astronomical surveys.
  • Experience using Jira, Confluence and LaTeX.      

Application reviews will begin immediately and continue through March 31, 2019 or until the position is filled.

AURA provides a generous compensation package including health coverage, paid time off and retirement benefits.  Starting salary will be commensurate with qualifications and experience.

AURA, as a leader in the astronomical community, is committed to diversity and inclusion. AURA develops and supports programs that advance our organizational commitment to diversity, broaden participation, and encourage the advancement of diversity throughout the astronomical scientific workforce. Learn more at

As a recipient of U.S. Government funding, AURA is considered a government contractor and is subject to Equal Employment Opportunity and Affirmative Action regulations. As an Equal Opportunity and Affirmative Action Employer, AURA and all of the centers, do not discriminate based on race, sex, color, age, religion, national origin, sexual orientation, gender identity/gender identity expression, lawful political affiliations, veteran status, disability, and/or any other legally protected status under applicable federal, state, and local equal opportunity laws.

Veterans, disabled individuals or wounded warriors needing assistance with the employment process should request assistance at

Application Deadline: 
Friday, April 5, 2019
Current Status of Position: 
Accepting Applicants
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