Senior Geospatial Data Scientist

Doktar; Fatih; Hybrid; TRY 400,000 - 800,000; Full time

Benefits offered by this job

State-of-the-art facilities

Professional development

Performance bonus system

Company share options

Job summary

Doktar is seeking a Senior Geospatial Data Scientist to join our Istanbul-based hybrid team. You will contribute to basin-scale water stress assessments, climate-risk analytics, and geospatial modelling using satellite and climate data.

You will transform complex earth observation datasets into actionable insights, develop reproducible pipelines, and collaborate across AI/ML, geospatial, and sustainability initiatives.

Qualifications

• 5–7 years of experience in geospatial data science, remote sensing, Earth observation analytics, or GeoAI.
• Strong hands-on Python skills with data processing and modelling.
• Experience with Python-based geospatial workflows including GeoPandas, Rasterio, Xarray/Rioxarray, GDAL, Earth Engine, and QGIS.
• Solid understanding of raster and vector data processing and reproducible analytical workflows.
• Familiarity with satellite and climate datasets such as Sentinel, Landsat, MODIS, GRACE, ERA5, CHIRPS.

Responsibilities

• Develop and maintain remote sensing workflows for water, climate, and agricultural analytics.
• Work with satellite datasets such as Sentinel, Landsat, MODIS, GRACE, ERA5, and CHIRPS.
• Support basin-scale analyses including evapotranspiration, water balance, drought, groundwater.
• Process and analyze raster and vector geospatial data using Python and geospatial tools.
• Build reproducible processing pipelines and automate analysis workflows.
• Within the Data Science team, work across AI/ML, geospatial, and sustainability initiatives to convert environmental signals into practical insights for field operations and sustainability programs.
• Support interpretation, visualization, and technical reporting of environmental and hydro- climatic analyses.
• Contribute to methodology development for satellite-driven sustainability and water-risk assessments.

Skills

Geospatial data science

Remote sensing

Earth observation analytics

GeoAI

Python programming

Data analysis

Tools

GeoPandas

Rasterio

Xarray/Rioxarray

GDAL

Google Earth Engine

QGIS

PostGIS

Docker

Job description

Homepage

Career

Senior Geospatial Data Scientist

Senior Geospatial Data Scientist

Hybrid Istanbul

About Doktar

Headquartered in the Netherlands and operating globally, Doktar develops data-driven technologies that enable climate-smart and sustainable agriculture.

Our technologies, digital platforms, and sustainability advisory services help farmers, corporations, and governments improve productivity while protecting the planet.

The Opportunity

In this role, you will contribute to basin-scale water stress assessments, climate-risk analytics, groundwater and evapotranspiration analysis, and geospatial modelling workflows using satellite and climate datasets.

You’ll work on real-world environmental challenges by combining remote sensing, hydrology, geospatial analytics, and data science methodologies to support scalable and scientifically grounded decision-making systems.

This role is ideal for candidates who enjoy transforming complex earth observation datasets into interpretable and actionable insights.

What You’ll Do

• Develop and maintain remote sensing workflows for water, climate, and agricultural analytics.

• Work with satellite datasets such as Sentinel, Landsat, MODIS, GRACE, ERA5, and CHIRPS.

• Support basin-scale analysis including evapotranspiration, water balance, drought, groundwater, and crop-water-stress assessments.

• Process and analyze raster and vector geospatial datasets using Python and geospatial tools.

• Build reproducible geospatial processing pipelines and automate analysis workflows.

• Within the Data Science team, work across AI/ML, geospatial, and sustainability initiatives to convert environmental signals into practical insights for field operations and sustainability programs.

• Support interpretation, visualization, and technical reporting of environmental and hydro- climatic analyses.

• Contribute to methodology development for satellite-driven sustainability and water-risk assessments.

What We’re Looking For

• 5–7 years of experience in geospatial data science, remote sensing, Earth observation analytics, or GeoAI, ideally with exposure to agriculture, water, climate, or environmental applications.

• Strong hands‑on Python skills, with experience using scientific and geospatial libraries for data processing, analysis, and modelling.

• Experience with Python-based geospatial and Earth observation workflows, including tools such as GeoPandas, Rasterio, Xarray/Rioxarray, GDAL, Google Earth Engine, and QGIS.

• Solid understanding of raster and vector data processing, spatial analysis, map algebra, geospatial data pipelines, and reproducible analytical workflows.

• Familiarity with satellite and climate datasets such as Sentinel, Landsat, MODIS, GRACE, ERA5, CHIRPS, or similar open Earth observation datasets.

• Understanding of statistics, time‑series analysis, and spatial modelling, with the ability to translate complex environmental datasets into meaningful insights.

• Knowledge of environmental systems, hydrology, water balance, evapotranspiration, drought, groundwater, or climate‑risk analytics is highly preferred.

• Ability to communicate technical findings clearly through visualizations, technical reports, methodology notes, and stakeholder‑facing explanations.

• Familiarity with cloud platforms, Docker, PostGIS, or scalable data processing environments is a plus.

• Strong analytical thinking, scientific curiosity, and ownership mindset, with the ability to work on complex, real‑world environmental problems in a collaborative Data Science team.

What we offer

• An interesting and highly responsible role in a young and interdisciplinary team.

• State‑of‑the‑art technical facilities (software and communication tools).

• Professional development opportunities.

• Performance‑bonus system.

• Company share options.