Agroecosystem Specialist Varaha Reversing climate change through conscious nature-based interve[...]

AgFunder; Gurgaon; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Varaha is seeking an Agroecosystem Specialist to strengthen agronomic and crop modeling science for carbon projects. You will translate agroecosystem dynamics into defensible model parameterization and literature-backed documentation, working closely with the Modeling Lead and the Science team.

The role involves literature reviews, model calibration, data curation, and contributions to Project Design Documents and Monitoring Reports, with emphasis on Indian cropping systems and smallholder

Qualifications

• Master’s degree in agronomy, soil science, or related field with modeling focus.
• Deep knowledge of Indian cropping systems and smallholder management variability.
• Hands-on experience with DayCent, DNDC, or RothC modeling.
• Ability to conduct literature reviews and extract quantitative data for modeling.
• Clear scientific writing in English with traceable citations.

Responsibilities

• Lead literature review to inform model parameterization and methodology.
• Support calibration and debugging of biogeochemical models.
• Curate agronomic datasets for production modeling runs.
• Debug DayCent, DNDC, and RothC runs; document analyses.
• Contribute to Model Validation Reports and related documents.
• Track updates to Verra, Gold Standard, and Isometric methodologies.

Skills

Structured literature reviews

Scientific documentation

Traceable data extraction

Education

Master's degree in agronomy or related field

Tools

Python (pandas, numpy)

Git

DayCent/DNDC/RothC

Job description

Varaha is hiring an Agroecosystem Specialist to strengthen the agronomic and crop modeling science behind our carbon projects. We are looking for someone with deep knowledge of Indian and South/Southeast Asian cropping systems. This person should be able to translate agroecosystem dynamics into defensible model parameterization and literature-backed scientific documentation.

You will work closely with the Modeling Lead and the broader Science team. This role will lead scientific literature review to inform model parameterization and methodology decisions, support calibration and debugging of biogeochemical models, and curate the agronomic datasets that underpin production modeling runs.

What you will own

• Crop system characterization and agroecosystem parameter selection for DayCent, DNDC and RothC runs — with particular depth in Indian smallholder systems (rice, wheat, maize, pulses) and their management practice variability.
• Systematic literature review and data extraction to support model parameterization, baseline construction, and methodology applicability assessments structured, traceable, and audit-ready.
• Curation and QA of agronomic and environmental datasets used in calibration and validation runs, including identification and resolution of data quality issues upstream of modeling.
• First‑line debugging of DayCent, DNDC, and RothC model runs diagnosing failed runs, anomalous outputs, and parameter inconsistencies, and escalating with documented analysis.
• Scientific writing contributions to Model Validation Reports, Project Design Documents, and Monitoring Reports particularly sections requiring agronomic narrative, literature citations, or parameter justification.
• Tracking relevant updates to Verra (VCS), Gold Standard, and Isometric methodologies flagging changes that affect model inputs, baseline assumptions, or data collection requirements.

What we’re looking for

• Master’s degree in agronomy, soil science, agricultural science, environmental science, or a closely related field with a research focus on cropping system modeling or agroecosystem dynamics.
• Deep working knowledge of Indian cropping systems: dominant crops, seasonal calendars, irrigation practices, soil types, and management variability across major agricultural zones.
• Hands‑on experience with at least one process‑based biogeochemical model (DayCent, DNDC, RothC, or comparable) running, debugging, and interpreting outputs.
• Demonstrated ability to conduct structured scientific literature reviews and extract quantitative data for modeling or methodology applications.
• Clear scientific writing in English, ability to produce traceable, well‑cited documentation suitable for registry or VVB review.

Requirements

• Experience with smallholder systems beyond India.
• Familiarity with Verra VM0042, VMD0053, or equivalent carbon registry methodologies.
• Production‑quality Python for data processing and analysis (pandas, numpy); comfort with version‑controlled workflows (Git).
• Prior exposure to carbon project workflows PDDs, MRs, or model validation documentation.
• Experience integrating LLM‑assisted workflows into literature review, data extraction, or scientific documentation.

We hire for strategic alignment and cultural fit. If you bring exceptional capability with slightly more or less experience than the band above, we’d still like to hear from you.