Role Overview
We are looking for a detail-oriented Data Analyst cum GIS Analyst to play a critical role in our carbon credit project development pipeline. You will focus on analyzing agricultural, environmental, and geospatial data, performing rigorous quality checks, and ensuring data readiness and integrity for project filing, third-party validation, and credit issuance. This is not a data engineering or machine learning role.
Key Responsibilities
- Collect, clean, validate, and perform QA on field data (soil samples, farm practices, yield records), satellite/remote sensing data, and other monitoring datasets.
- Conduct spatial data analysis and GIS mapping for project boundaries, land-use stratification, baseline mapping, and monitoring of regenerative practices (e.g., reduced tillage, cover cropping, crop rotation).
- Integrate ground-truth data with geospatial layers to support accurate project area delineation and sampling design.
- Prepare high-quality datasets, reports, visualizations, maps, and summaries required for Project Design Documents (PDD), monitoring reports, and submission to carbon registries (Verra, Gold Standard, etc.).
- Ensure all data meets the requirements of relevant methodologies (e.g., Verra VM0042 or equivalent soil carbon methodologies) and dMRV standards for audit-readiness and credit issuance.
- Identify data gaps, anomalies, or inconsistencies and coordinate with field teams for resolution.
- Maintain organized data repositories, documentation, and version control for traceability and compliance.
- Collaborate with field agronomists, project developers, and the Data Engineering / AI/ML teams to support end-to-end project development.
- Generate dashboards and spatial visualizations to communicate insights internally and for stakeholder reporting.
Key Skills Qualifications
- Strong proficiency in GIS software (QGIS, ArcGIS Pro/ArcMap) and spatial analysis tools/techniques.
- Advanced data analysis skills using Python (pandas, GeoPandas, matplotlib/seaborn), SQL, and Excel/Google Sheets (advanced functions, pivot tables, VBA optional).
- Experience in data cleaning, validation, QA/QC processes, and data quality frameworks.
- Hands-on experience working with geospatial data formats(shapefiles, GeoJSON, rasters, vector layers) and basic remote sensing imagery (Sentinel, Landsat, etc.).
- Excellent attention to detail and ability to ensure data accuracy for regulatory/compliance purposes.
- Strong written and verbal communication skills for preparing reports and presenting findings.
Preferred Qualifications
- 4 -7 years of relevant experience in GIS and/or data analysis, ideally in agriculture, environmental science, sustainability, or carbon projects.
- Bachelor’s or Master’s degree in GIS, Remote Sensing, Environmental Science, Agriculture, Data Analytics, or a related field.
- Familiarity with carbon credit standards, methodologies (especially Verra VM0042 or similar SOC-focused methods), MRV processes, and project filing requirements.
- Understanding of regenerative agriculture practices and basic soil science/carbon sequestration concepts.
- Experience with data visualization tools (Power BI, Tableau, or similar) and version control (Git basic).
- Prior exposure to dMRV platforms or digital tools in agriculture/carbon space is a strong plus.
Your data directly powers verified carbon credits and better livelihoods for thousands of farmers across India
Competitive salary + ESOPs - grow financially as Prithu scales
Flexible working hours + WFH - we trust you to own your time
Cutting-edge exposure - work with global carbon registries, blockchain MRV, and remote sensing at the frontier of climate tech
High-ownership culture - small team, flat structure, your work is visible and valued
