12795 - Observations & Earth Observation Data Analyst

Observations & Earth Observation Data AnalystDeadline: November, 19th, 2025What We Are Looking ForWe are seeking an Observations & Earth Observation (EO) Data Analyst to join the PRESTO research unit within the Regional Models and Geo‑Hydrological Impacts (REMHI) division. The ideal candidate blends expertise in satellite/EO data, ground‑based observations, and sensor networks, climate data processing (NetCDF, raster), GIS, and Python/R on UNIX/Linux. The role will design reproducible workflows to ingest, quality‑control, and integrate observational datasets with climate/impact model outputs, enabling user‑centred climate services, nowcasting, and monitoring applications.About UsCMCC Foundation is a cross‑cutting scientific research centre on climate change and its interactions with the environment, society, business, and policymakers. Our work aims to stimulate sustainable growth, protect the environment, and develop strategies for the adaptation and mitigation of climate change. CMCC’s core objective is to conduct cutting‑edge science, train the next generation of scientists at national and international levels, and serve as a beacon for climate modelling. We pursue fundamental and applied science with utmost scientific integrity, prioritising data‑driven science and providing data, information, and research results that support informed public debate and decision‑making processes. CMCC invests in training all our talents and strives to create a workplace where everyone can excel. At CMCC you will find a strong, professional environment and an inclusive community that values diversity. We foster a culture of innovation and societal change, where individuals from all backgrounds can thrive and succeed.RoleThis role strengthens PRESTO’s operational capability on observational data and its integration with EO/climate information across applications such as heavy precipitation and lightning monitoring, fire and drought indicators, health and urban services. The position supports the ingestion, curation, and publication of observations, bridging in‑situ sensors, EO products, and numerical model data to feed decision‑support tools (e.g., Dataclime) and operational services (e.g., dashboards, APIs, web services).ResponsibilitiesIngest, process, and analyse observational datasets (in‑situ weather stations, radars) and Earth Observation data (e.g., optical/SAR) alongside atmospheric numerical modelled datasets (e.g., NetCDF, GeoTIFF).Design and maintain data pipelines on UNIX/Linux using Python/R (xarray, pandas, NumPy) and climate utilities (CDO/NCO), ensuring adequate documentation.Implement quality control (QC), calibration/validation and metadata standards for observational harmonised multi‑source datasets for monitoring and nowcasting.Perform spatial analysis using machine‑learning tools to support applications based on weather models and data.Publish and catalogue datasets/services through ERDDAP and GeoServer; support interoperable access via API and standard protocols (OGC).Collaborate with interdisciplinary teams to co‑design user‑centred indicators and dashboards for REMHI; prepare technical material for stakeholder workshops and demos.Contribute to deliverables, technical reports and (where relevant) peer‑reviewed publications; present results at meetings and conferences.Support field activities in coordination with technical staff (e.g., sensor deployment/maintenance planning, data retrieval logistics) when required.RequirementsM.Sc. (or equivalent) in Earth/Environmental Sciences, Physics, Engineering, Computer Science, or related fields.Strong experience with Python for EO/observational and climate data processing (xarray, pandas, NumPy; Jupyter); familiarity with R is a plus.Proficiency with GIS (QGIS/ArcGIS) and spatial analysis; knowledge of formats/standards (NetCDF, GeoTIFF, HDF, CSV time series).Hands‑on experience with UNIX/Linux, CDO/NCO, and automated batch processing for large datasets.Experience with ERDDAP/GeoServer (or similar) for data publication; basic web‑mapping literacy and API usage.Knowledge of machine‑learning methods for image/time‑series classification and basic statistics for environmental applications.Excellent teamwork and communication skills in English; Italian fluency is a plus for field/stakeholder interactions.Additional SkillsFamiliarity with observational networks (meteorological stations, hydrological gauges, low‑cost sensors) and data QC protocols.Experience with SAR processing and cloud‑based EO platforms; containerisation (Docker) is a plus.Database literacy (SQL/PostGIS) and API‑based data access; experience with CI (GitHub) and simple ETL/ELT orchestration.Experience preparing technical documentation, deliverables, and visual communication of results.Duration, Compensation & BenefitsOpportunity will be offered both internally and externally.Researcher will be based in Caserta (CMCC office), with flexible working arrangements according to internal policies.Contract and gross annual salary will be based on qualifications and working experience.Welfare package for a minimum 12‑month contract.Flexible working time as per internal policies.Support during the immigration process, if needed.For outstanding profiles, open to part‑time arrangements and remote work.Protected CategoryBelonging to legally protected categories (e.g., L. 68/99) will constitute a preferential condition. Some fiscal benefits could be applied for repatriated workers or foreign researchers/professors, having the requirements defined by Dlgs 147/2015 (for repatriates) or Dl 78/2010 (for foreigners).Equal Opportunity StatementCMCC is an equal‑opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status, and other legally protected characteristics. Please omit from your CV any data you or we might consider discriminatory.ApplicationThis job announcement is an invitation to express interest in the above‑mentioned CMCC Position. To learn more about this opportunity and submit your application, please refer to the following: (application instructions here).#J-18808-Ljbffr