Ecological Systems Developer

19 hours ago

Gulbarga, Karnataka, India beBeeEcosystem Full time ₹ 90,00,000 - ₹ 1,20,00,000
Job Description

This is a unique opportunity for an experienced environmental modeller with strong programming expertise to develop, implement and maintain components of the ecosystem model.

The role involves translating complex modelling concepts into robust, production-ready code that enhances the ability to make accurate predictions of soil carbon levels and agricultural system interactions.

Key responsibilities include working with agricultural ecosystem models, implementing and maintaining integration between different components, ensuring seamless data flow and contributing to the development of the Bayesian data assimilation framework.

Required Skills and Qualifications

Advanced Programming Skills: Extensive experience in Python programming for data science and environmental modelling, including proficiency with scientific libraries (NumPy, SciPy, Pandas, scikit-learn, GeoPandas) and Bayesian statistical libraries (PyMC or similar).

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, including model validation and statistical analysis.

Code Quality Focus: Experience with software development best practices including version control (Git), 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: Master's degree or PhD in Data Science, Environmental Science, Computer Science, or related field with a strong focus on modelling and programming.

Benefits

The successful candidate will have the opportunity to work independently and as part of a multi-disciplinary team, reflecting engineering, GIS, soil science, quality management, and data systems.

They will also have the chance to collaborate effectively with external partners and communicate technical modelling concepts and results to both technical and non-technical audiences.

Others

The ideal candidate will have a track record of peer-reviewed publications in relevant fields and be familiar with geospatial data handling, containerisation and deployment technologies.

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