Weather Modeling and Data Scientist

Website BASF

We Create Chemistry

We are currently seeking a Weather Modeling and Data Scientist to join our team. The selected individual will use and apply spatio-temporal statistics, machine learning, mechanistic modeling and other approaches to continuously improve our weather and agricultural models. The Weather Modeling and Data Scientist serves as an expert on physical models, and their output data, for use in agricultural applications. He or she will interface with the company’s weather analytics and agricultural modeling teams. Position seniority and compensation will depend on the level of a candidate’s expertise and experience. The position will require occasional short-term travels in the United States and internationally.

  • You will use your advanced degree (MS) in Atmospheric Science, Meteorology, Oceanography, Engineering or related physical sciences. BS degree with sufficient background and qualifications will be considered.
  • Use your 3+ years of experience operating, evaluating, and/or developing physical numerical models for the atmosphere, ocean, or other disciplines
  • Use your 3+ years of experience using advanced statistical analysis techniques to improve, compare, and validate output data from physical numerical models
  • Use your 3+ years of using big data and cloud computing solutions to manipulate large spatial gridded data in the most efficient manner
  • Experience with regional and/or global numerical weather prediction models (WRF, HRRR, NAM, GFS, ECMWF, etc.) for research and/or operational applications
  • Fluent in at least one programing language appropriate to the needs of the weather department, e.g., C, C++ , Python, FORTRAN, Perl, or shell scripting
  • Strong working knowledge and experience using R, SAS, MATLAB, or similar packages for statistical analysis
  • Ability to write well-structured, easily maintainable, and well-documented code that executes very efficiently as part of overall data processing optimization
  • A drive to solve problems, meet deadlines, and build whatever is necessary along the way
  • Familiarity with observational and model data quality control, analysis, interpretation, integration, and visualization using various tools and methods 

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