Job Description Summary :
Responsible for developing and applying spatial data analysis and geostatistical models to support oil palm research. Key tasks include designing sampling strategies, automating data processing (R/Python, GIS), integrating remote sensing data, managing spatial databases, and translating analytical insights into practical field recommendations
Job Description :
Design robust sampling strategies for spatial data collection, including but not limited to soil properties, yield, climate, and drone/remote sensing imagery.
Develop scripts and tools using programming languages (e.g., R, Python) and GIS platforms (ArcGIS/QGIS) to automate data processing, modeling, and analytical workflows.
Integrate and process remote sensing and satellite imagery into existing spatial models to enhance prediction accuracy and coverage.
Contribute to the maintenance and management of large-scale spatial databases (GIS layers, remote sensing data, etc.).
Apply sophisticated geostatistical techniques, such as variogram modeling, Kriging, spatial interpolation, and simulation, to raw research data.
Analyze and interpret spatial variability in the yield, soil characteristics, nutrient status, and pest/disease incidence.
Collaborate closely with Biometrician, GIS specialists, agronomists, plant breeders, pest and disease, and other researchers to translate analytical findings into practical, actionable recommendations.
Conduct continuous research to improve and validate spatial analysis methodologies specific to oil palm cultivation.
Support decision-making by effectively presenting complex findings using clear, impactful visual formats (e.g., thematic maps, dynamic dashboards, comprehensive reports).
Provide specialized training to R&D and field staff on spatial considerations for accurate data handling and interpretation.
Job Requirement :
Minimum Bachelor’s or Master’s degree in Statistics, Geo-Statistics, Data Science, Spatial Science, or a closely related field.
Strong foundational knowledge in statistical principles, Geographic Information Systems (GIS), remote sensing, and data analysis.
Proficiency in statistical programming and software (specifically R and/or Python) for spatial data manipulation and modeling.
Proficiency in professional GIS software (ArcGIS and/or QGIS).
Demonstrated experience with database management systems (SQL) for data querying and retrieval.
Proven experience in spatial modeling, geostatistical analysis, and handling big data (especially environmental or agricultural datasets).
Excellent analytical, quantitative, and problem-solving abilities with meticulous attention to detail.
Effective communication and presentation skills for conveying complex geostatistical data and research findings to both technical and non-technical stakeholders.
Ability to work both independently and collaboratively as a key member of a multidisciplinary R&D team.
Willingness to be permanently located at the SMART Research Institute in Libo, Kandis, Riau.
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