Satellite Applications Specialist - Precipitation

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{
  "lists": [
    {
      "text": "What You'll Do",
      "content": "<li><b>Data Acquisition:</b> Identify and access publicly available meteorological satellite data from various platforms (e.g., GOES, Meteosat, MODIS, Sentinel, etc.). Develop and maintain data acquisition workflows to retrieve large multi-spectral datasets. Implement data storage and management strategies.</li><li><b>Data Ingestion and Processing:</b> Ingest satellite data into data processing systems. Perform data quality checks. Define and implement correction methodologies. Apply atmospheric correction algorithms to account for the effects of the atmosphere on satellite measurements. Develop and implement advanced algorithms for quantitative precipitation estimation (QPE) and phase classification based on machine learning methods.</li><li><b>Data Analysis:</b> Analyze satellite data to extract meteorological information, such as cloud cover, precipitation intensity, cloud phase, and atmospheric temperature and humidity profiles. Work to analyze real-time and archival case studies. Develop and apply data visualization techniques to represent meteorological phenomena. Contribute to scientific research projects and publish findings in peer-reviewed journals.</li><li><b>Algorithm Development:</b> Develop and test new algorithms for satellite data processing and analysis. Collaborate with data scientists and meteorologists to improve existing algorithms. Stay up-to-date on the latest advancements in satellite remote sensing and data analysis techniques.</li><li><b>Precipitation Enhancement Applications: </b>Support precipitation enhancement operations by providing satellite data analysis to identify suitable cloud targets and assess the effectiveness of seeding efforts. Develop algorithms to estimate the potential for precipitation enhancement from precipitation enhancement.</li>"
    },
    {
      "text": "Required Qualifications",
      "content": "<li>Master's degree or Ph.D. in meteorology, atmospheric science, remote sensing, or a related field.</li><li>Strong understanding of satellite remote sensing principles and meteorological processes.</li><li>Experience with data acquisition, processing, and analysis of large datasets. This involves distributed computing methods, database management systems, data partitioning, vectorizing operations, and GPU acceleration.</li><li>Experience with Amazon Web Services cloud computing for external data sources, and internal instance management.</li><li>Proficiency in data analysis tools and programming languages (e.g., Python, MATLAB, R, C++).Knowledge of machine learning and deep learning techniques, for satellite applications.</li>"
    }
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  "country": "US",
  "createdAt": 1724968805570,
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    "team": "Science",
    "location": "El Segundo, CA",
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