Geospatial Data Science Analyst (Fixed-Term)

About the Role

The Geospatial Data Science Associate will work with different teams across the organization to support colleagues in thinking spatially about their work and uncovering patterns and revelations in their data analysis. You will be a part of the Global Impact Team and will report to the Global Remote Sensing Manager. 

Responsibilities

• You'll support data analysis and visualization for several geospatial and remote sensing projects including yield modeling, optimized agronomy, and above-ground biomass measurement.
• You'll research, summarize, and critically evaluate the feasibility of emerging technologies for remote sensing data for agricultural use cases
• You'll support the design and creation of maps, dashboards, and other visual data presentations.
• You'll build technical capacity across the organization for using geospatial datasets to inform decisions and assess impact.
• You'll train and upskill new team members to familiarize them with One Acre Fund's data management processes and options for analysis.

Career Growth and Development

We have a strong culture of constant learning and we invest in developing our people. You’ll have weekly check-ins with your manager, access to mentorship and training programs, and regular feedback on your performance. We hold career reviews every six months and set aside time to discuss your aspirations and career goals. You’ll have the opportunity to shape a growing organization and build a rewarding long-term career.

Qualifications

Across all roles, these are the general qualifications we look for. For this role specifically, you will have:

• 4+ years of experience in data science, statistics, cartography, or remote sensing for agricultural or environmental fields.
• University degree in a related field (e.g. Data Science, Environmental Science + GIS)
• Experience analyzing, organizing, and visualizing diverse datasets
• Ability to communicate technical skills to diverse audiences.
• Proficiency in GIS and programming languages including R and Python.
• Skills in cartographic data visualization are a plus.