Senior Environmental Model Developer

4 days ago

Mysore, Karnataka, India beBeeEcosystem Full time ₹ 20,00,000 - ₹ 25,00,000

As a distinguished environmental modeler, you will have the opportunity to collaborate with our team in developing and implementing cutting-edge ecosystem models.

We are seeking an expert with extensive experience in Python programming for data science and environmental modeling. The ideal candidate should have a strong background in scientific libraries such as NumPy, SciPy, Pandas, scikit-learn, and GeoPandas, as well as proficiency in Bayesian statistical libraries like PyMC or similar.

The role involves working with agricultural ecosystem models, including plant growth models (LINTUL-5, LINGRA), soil organic carbon models (RothPC, RothPC-N), soil water models, mineral nitrogen models, and grazing models.

Key responsibilities include:

Model Development

Configuring, running, and extending existing model components such as LINTUL-5 (arable crops), LINGRA (grass), RothPC-N (soil organic carbon and nitrogen), and developing Python implementations that maximize the benefit of our access to the world's largest soil carbon database.

Implementing machine learning and statistical models using Python libraries to enhance overall accuracy and predictive power, potentially as part of ensemble modelling approaches.

Collaboration and Communication

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

Producing comprehensive technical documentation, code comments, and user guides for all modelling implementations.

Communicating technical modelling concepts and results to both technical and non-technical audiences, including partners and stakeholders.

Requirements

Advanced programming skills with extensive experience in Python programming for data science and environmental modeling.

Environmental modelling experience, preferably with ecosystem models or related areas.

Data science proficiency with machine learning techniques and their application to environmental data, including model validation and statistical analysis.

Code quality focus with experience in software development best practices, including version control (Git), testing frameworks, and code documentation.

Excellent analytical and problem-solving abilities with extreme attention to detail and a rigorous approach to model development.

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

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