HabiTerre provides in-depth intelligence for agricultural land, including crop, water, nutrients, and carbon, from aboveground to belowground. Launched out of a world-class research lab at the University of Illinois, HabiTerre generates unprecedented field-scale intelligence for businesses in the food and agriculture industry. HabiTerre carries an ambitious mission to de-risk and sustain modern agriculture for humanity.

We use process-based models, remote sensing, and artificial intelligence to evaluate past, present, and future cropland performance, including crop rotation, management history, yield, water use, nutrient dynamics, and carbon sequestration. With a methodology that starts at the field level, allowing aggregation across any global region, we offer critical insights to businesses throughout the agriculture value chain.

Work Environment

We are an equal opportunity employer with a team around the country. We offer a workplace that is both casual and professional and a culture that is committed to learning, fun, and excellence.

Our team consists of people who are passionate about creating insights-rich and intuitive customer experiences and, at the same time, obsess over performance and reliability of what we build. We challenge the status quo and strive to find the best way to solve problems.

The successful candidate will join our R&D team, which consists of a group of leading scientists and engineers in earth system modeling, remote sensing, software engineering and artificial intelligence. We work in small collaborative groups to keep things simple and efficient, and thus give a lot of autonomy to our staff members to perform the work required and be creative. Apply for this position now on LinkedIn.

Environmental Modeler – Job Responsibilities

• Conduct necessary R&D efforts to apply process-based carbon and land models to various agricultural systems, including both row cropping systems and pastureland systems, to quantify agricultural outcomes (including productivity and environmental impacts, such as greenhouse gas emissions and soil carbon change).
• Develop scalable computation pipelines for process-based carbon and land models and integrate different sources of satellite data, in a high-performance computing environment (e.g. supercomputer and/or cloud computing platforms).

[Note: Major single components have been developed and tested; the major task here is to integrate different components to optimize computation efficiency.]

• Conduct model simulation and uncertainty analysis and ensure QA/QC.
• Handle data manipulation and visualization and administration of systems in accordance with enterprise data security protocols and privacy policy.
• Document code and results and draft scientific reports for generated results.
• Work with product management and the R&D team to productize.
• Generate deliverables upon customers’ requests and work to address customer needs and feedback.
• Effectively communicate scientific outcomes with the company business team and customers. Automate and simplify team development, testing, and operations processes.
• Provide necessary support to the company’s intellectual property counsel.

Basic Qualifications:

• Master in Earth Science, Environmental Science/Engineering, Atmospheric Science, Hydrological Science, or related technical field.
• 3+ Years of experience in Python development and scientific data visualization.
• 3+ Years of experience in using ecosystem or climate models or using model outputs.
• Proficiency with Linux/UNIX and Shell scripting and high-performance computing. Comfortable with multi-tasking and working as part of a team.

Preferred Qualifications: (fulfilling two or more)

• PhD degree in Earth Science, Environmental Science/Engineering, Atmospheric Science, Hydrological Science, or related technical field.
• Experience in process-based earth system models, ecosystem models, and/or biogeochemistry models.
• Experience in satellite remote sensing and geospatial data processing.
• Experience in model-data fusion methods, such as calibration, data assimilation, etc.
• Experience with MPI or other parallel computing architectures.
• Experience in developing and releasing highly scalable products.
• Possession of excellent oral and written technical communication skills.
• 2+ Years experience of implementing large-scale data processing and modeling pipelines on cloud computing platforms such as AWS, GCP and Azure.
• Experience in implementing basic machine learning algorithms using Python ML/DL frameworks, such as PyTorch, Tensorflow, Scikit-Learn.
• Experience with developer’s tools, such as Pycharm, Jupyter, Spyder, Git, etc.

Other Considerations

• Industry-level competitive compensation, based upon relevant experience.
• This position provides stock options.
• This position considers sponsoring H1B visa applications for qualified international applicants.