Geospatial Data Scientist

São Paulo, BR, Brazil

Full Time

Data Science

Mid Level

EarthDaily Agro provides space age data and analytics to the organizations and people who feed the planet

With 35 years of industry experience, EarthDaily Agro provides customers with the data, analysis and knowledge they need to make more efficient and effective decisions. B2B services range from global risk management and monitoring of agricultural commodities to the marketing of inputs and precision agriculture consulting, using the latest research in agronomy, information technologies and remote sensing.

EarthDaily Agro also develops highly customized business solutions for agricultural lenders, insurers, input suppliers and food companies, with easy-to-use analytics, that help reduce the daily risks of agriculture.

EarthDaily Agro is headquartered in Minneapolis, MN, USA, with offices in France, Brazil, Australia and is a division of EarthDaily Analytics Corp.

EarthDaily Analytics Corp., a vertically-integrated data processing and analytics company, is launching a new constellation of earth observation satellites. The EarthDaily satellite constellation will significantly enhance geospatial analytics capabilities in agriculture, forestry, environment, financial services, and intelligence, among many other verticals.

Join us in revolutionizing the agricultural sector with geospatial intelligence

As GEOSPATIAL DATA SCIENTIST, you will be responsible for processing, analyzing, and interpreting geospatial data derived from satellite imagery, remote sensing technologies, and meteorological sources. You will work closely with data engineers, agronomists, and software developers to create predictive models and decision-support tools tailored for the agricultural sector.

Based in Brazil, you will report to our local Brazilian Data Scientist Team Manager but will be part of an international team with colleagues in France and USA.

YOUR KEY RESPONSIBILITIES INCLUDE:

• Develop and implement geospatial data analysis workflows, integrating satellite imagery, weather data, and agronomic datasets.
• Design and optimize machine learning models for applications such as crop health monitoring, yield prediction, and climate risk assessment.
• Utilize GIS and remote sensing techniques to extract meaningful insights for precision agriculture or crop insurance solutions.
• Collaborate within an international Agile team (more than 6 nationalities), contributing to sprints, stand-ups, and code reviews.
• Work closely with software developers and data engineers to integrate geospatial models into operational products and APIs.
• Stay up to date with advancements in geospatial data science, remote sensing, and agricultural analytics.

Required qualifications:

• MSc or PhD in Geospatial Science, Remote Sensing, Data Science, Computer Science, or a related field.
• Proven experience (at least 3 years) with geospatial data processing, analysis, and visualization.
• Strong proficiency in Python and geospatial libraries such as GDAL, Rasterio, GeoPandas, and xarray.
• Experience with remote sensing techniques and platforms (e.g., Sentinel, Landsat, MODIS).
• Knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and statistical modeling.
• Familiarity with cloud computing environments (AWS, Google Cloud, or Azure) and big data processing.
• Strong communication skills and ability to work in an international, cross-functional team.
• Fluent in English (oral and written): meetings with clients and internal are mostly in English.

Bonus:

• Background in agriculture, agronomy, or environmental science.
• Experience with weather data processing and integration.
• Knowledge of deep learning techniques for geospatial applications.
• Familiarity with Agile development methodologies.
• Proficiency in database management for geospatial datasets.

CONDITIONS

Permanent, full-time job to start as soon as possible.

Job based in Sao Paolo, Brazil. Possibility of Flexible working arrangements (remote/hybrid).

Competitive salary and benefits package.

Continuous learning and professional development opportunities.

A dynamic, international, and collaborative work environment.

Apply now and be part of a forward-thinking team dedicated to data-driven innovation.