Science Data Quality and Operations Scientist
On-siteMadrid, Madrid, Spain
Madrid, Madrid, SpainOn-siteFull TimeDoctorate Or Professional DegreeEnterprise
Full TimeDoctorate Or Professional DegreeEnterprise
Job Summary
Monitor and assess the quality of scientific data products and processing chains for ESA missions in Astronomy, Planetary Science, and Heliophysics. Verify the integrity of incoming and outgoing mission products, analyze telemetry to identify anomalies, and coordinate corrective actions with instrument teams and software engineers. Support calibration, validation, and commissioning activities while producing quality assessment reports and operational documentation. Contribute to the definition of quality control procedures and participate in scientific reviews and validation campaigns.
Required Qualifications
- Degree in Physics, Astronomy, Space Science, Engineering or a related scientific discipline.
- Experience in scientific data analysis and interpretation.
- Understanding of scientific data processing workflows and product validation activities.
- Experience with Python and scientific data analysis libraries.
- Experience working in Linux environments.
- Ability to analyse complex scientific datasets and identify anomalies.
- Familiarity with scientific visualisation and Quick Look Analysis concepts.
- Understanding of instrument calibration principles and scientific product quality assessment.
- Strong analytical and problem-solving skills.
- Ability to work effectively with scientists, engineers and operational teams in an international environment.
- Good written and spoken English communication skills.
- Ability to work effectively in multidisciplinary teams and collaborate with a wide range of stakeholders.
Desired Qualifications
- Previous experience with Science Operations Centres or scientific ground segment activities.
- Experience supporting astronomy, planetary science, heliophysics or Earth observation missions.
- Experience with commissioning, calibration or validation campaigns.
- Knowledge of FITS, PDS, CDF, NetCDF or similar scientific data formats.
- Experience with Python scientific ecosystems (NumPy, SciPy, Pandas, Matplotlib, Astropy).
- Knowledge of scientific archives and data dissemination systems.
- Experience with SQL, scripting and software quality verification activities.
- Familiarity with Agile methodologies and collaborative engineering tools such as Jira and Confluence.
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