Senior Geospatial Data Scientist

Meridia

. Develop accurate, high-quality models and datasets for production area assessment and sourcing area (supply shed) analysis across multiple commodities and origin countries .

Posted 10/16/2026contractRemote • NetherlandsSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing high-quality models and datasets for agricultural supply chain analysis, leveraging advanced statistical techniques and geospatial data engineering. Proficient in Python, R, and Google Earth Engine, with a strong focus on documentation and reproducibility in analytical methodologies.

Highest-signal resume keywords

Advanced Degree In Remote SensingProficiency In PythonGeospatial Data Engineering SkillsExperience With Supply Chain ModellingStrong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical TechniquesEarth Observation TechniquesMachine Learning ModelsModelling ApproachesData ProvenanceVersion-Controlled Analytical PipelinesValidation Against Ground-Truth DataProduction StatisticsYield Data AnalysisDocumentation Of Methodologies

Soft Skills

Strong Communication SkillsAbility To Work Independently

Tools & Technologies

Google Earth EnginePostGISGDALGeopandasGitDocker

Industry Keywords

Agricultural SystemsSupply ChainsAgri-Commodity SectorsSupply Chain TransparencyTraceability ApproachesEUDRDCF/NDPECertification SchemesRisk AssessmentData-Scarce Environments

Tech Stack

Tools & technologies

DockerPostGISPythonRemote Sensing

About the role

Key responsibilities & impact

Develop accurate, high-quality models and datasets for production area assessment and sourcing area (supply shed) analysis across multiple commodities and origin countries
Leverage Meridia's in-situ farm plot datasets to train and validate models
Adapt existing machine learning models to local agricultural contexts to improve prediction accuracy
Create scalable and reproducible methodologies across different geographies and commodities
Produce a methodology and codebase
Organise all source files
Provide full documentation covering operating workflow, methodology, data sources, retrieval and licensing details
Support first-mile intelligence connecting commodity supply chains to production areas through production area assessment, supply shed modelling and traceability

Requirements

What you’ll need

Advanced degree (MSc or PhD) in Remote Sensing, Geospatial Science, Computer Science, or related field
10+ years of practical experience in applying statistical and earth observation techniques to agricultural applications
Proficiency in Python, R, and Google Earth Engine
Knowledge of agricultural systems and supply chains in tropical and subtropical regions
Experience with modelling approaches relevant to supply chain analysis, such as optimisation, spatial allocation, entity matching or network analysis across heterogeneous datasets
Strong geospatial data engineering skills, including spatial databases such as PostGIS, GDAL/geopandas or equivalent, and handling large raster and vector datasets
Experience building reproducible, version-controlled analytical pipelines using Git; Docker/containerisation is a plus
Proven ability to document methodologies rigorously, including data provenance, assumptions, limitations and licensing
Ability to work independently in a remote setting
Strong communication skills and full professional proficiency in English
Familiarity with agri-commodity sectors and their data landscape is nice to have
Familiarity with agricultural supply chain transparency and traceability approaches, logistics, procurement and certification is nice to have
Working knowledge of EUDR, DCF/NDPE, certification schemes and related risk assessment is nice to have
Experience validating models against ground-truth or in-situ field data and communicating uncertainty is nice to have
Experience with production statistics and yield data in data-scarce environments is nice to have
Peer-reviewed publications or public technical documentation in a related domain is nice to have
Prior experience in Southeast Asia and/or Latin America is nice to have

Benefits

Comp & perks

Initial 3-month engagement, with possible extension depending on progress and mutual fit
2-3 days per week
Fully remote
Software subscriptions provided by Meridia where applicable
Monthly invoicing against agreed milestones and deliverables
Work on a data lake covering 20%+ of the world’s agricultural land, alongside a team of 70+ agriculture, data and tech experts
Direct impact on EUDR, DCF and Scope 3 compliance work