Data Scientist AI Platforms

Function

We're looking for a skilled data scientist to join our client's team and contribute to various projects within the realm of remote sensing and artificial intelligence. This role involves operationalizing the next generation of GeoAI services and utilizing advances in large-scale Earth observation processing. Your expertise will be particularly valuable in developing crop type mapping algorithms critical for the agricultural sector.

Responsibilities

In this position, you will be tasked with:

• Operationalizing GeoAI services through the application of AI advances.
• Developing and improving machine learning and computer vision algorithms for large-scale remote sensing data processing, primarily focusing on Sentinel data.
• Scaling and maturing crop type mapping algorithms and solutions tailored to the digital agricultural landscape.
• Analyzing data streams and optimizing databases and queries to enhance performance.
• Engaging with stakeholders to communicate complex technical concepts.

Profile of the Ideal Candidate

The ideal candidate will possess a strong background in remote sensing data science, with demonstrated experience in:

• Developing geospatial foundation models.
• Deep learning frameworks, particularly in PyTorch, applied to geospatial or sensor data.
• Spatial databases like DuckDB and working with noisy tabular labeled data.
• Software engineering practices with a strong proficiency in Python and GIS applications (QGIS/ArcGIS, GDAL).
• Utilizing tools like dbt and Airflow for data processing.

You will need to have at least 5-7 years of experience in this field and an excellent command of English; knowledge of Dutch is not a requirement for this role.

Additional Requirements

Preference will be given to candidates who also possess:

• Experience with databases (SQL, Oracle) and reporting.
• Scripting experience in languages such as Shell, Perl, or Python.
• A proven academic background in the use of foundation models in remote sensing.
• A self-organized attitude complemented by strong analytical and communication skills for engaging both technical and non-technical stakeholders.