Modelling Sustainability Specialist

1 week ago

Gandhinagar, Gujarat, India beBeeenvironmentalmodeler Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

We are seeking a highly skilled Environmental Modeller to join our team.

Job Description

As an Environmental Modeller, you will be responsible for developing and implementing components of the Agricarbon Ecosystem Model (AEM) using Python.

You will work closely with our Principal Soil Modeller to translate scientific requirements into robust technical solutions, providing programming expertise to support complex modelling challenges.

The successful candidate will have extensive experience in Python programming for data science and environmental modelling, including proficiency with scientific libraries such as NumPy, SciPy, Pandas, scikit-learn, and GeoPandas, as well as Bayesian statistical libraries such as PyMC.

Key Responsibilities:
  • Develop and implement components of the AEM using Python.
  • Work closely with our Principal Soil Modeller to translate scientific requirements into robust technical solutions.
  • Provide programming expertise to support complex modelling challenges.
Requirements:
  • Advanced Programming Skills: Extensive experience in Python programming for data science and environmental modelling.
  • Environmental Modelling Experience: Proven experience developing and working with ecosystem models or related areas.
  • Data Science Proficiency: Extensive experience with machine learning techniques and their application to environmental data.
  • Code Quality Focus: Experience with software development best practices including version control, testing frameworks, and code documentation.
  • Problem-Solving Skills: Excellent analytical and problem-solving abilities with extreme attention to detail and a rigorous approach to model development.

Educational Background:

Masters degree or PhD in Data Science, Environmental Science, Computer Science, or related field with a strong focus on modelling and programming.

Nice to Have:
  • Experience with Bayesian methods and data assimilation frameworks.
  • Familiarity with soil carbon models such as RothC and crop growth models such as LINTUL, WOFOST, DSSAT, and APSIM.
  • Knowledge of nitrogen cycling and soil-plant-atmosphere interactions.
  • Familiarity with data assimilation using satellite-derived data.
  • Experience with cloud computing platforms for large-scale data processing.
  • Track record of peer-reviewed publications in relevant fields.
  • Geospatial data handling experience.

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