Christoph Rieke
ML Data Geo Engineer
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolChristoph Rieke is an ML Data Geo Engineer based in Berlin with 10 years of experience building geospatial data science and machine learning solutions across industry and research. He has led Python SDK development, integrated satellite and provider workflows, and delivered production-ready geospatial ML for clients at UP42 and Terra Labs, combining hands-on library work with product-facing responsibilities. His background in remote sensing and practical projects—from instance segmentation of agricultural fields to large-scale land cover and crop-type pipelines—gives him deep domain expertise in Earth observation and spatial analytics. An active open-source contributor, Christoph has improved popular mapping tools (prettymaps/prettymapp), fixing CRS issues, refactoring projections, and adding AOI and export features for OSM-based map generation. He’s as comfortable architecting data pipelines and SDKs as he is writing geometry-savvy Python, and he coordinates community efforts like GeoPython while hiring and mentoring teams.
10 years of coding experience
7 years of employment as a software developer
Master’s Degree Remote Sensing and Geoinformatics, Master’s Degree Remote Sensing and Geoinformatics at Friedrich Schiller University Jena
German, English
Stackoverflow
737reputation
42kreached
12answers
0questions
Github Skills (20)
openstreetmap10
lib10
pytest10
python10
matplotlib10
geopandas10
refactor10
cartography10
refactoring10
shapely10
streamlit9
maps9
generative-art7
shapefile6
geotiff6
Programming languages (8)
Github contributions (5)
chrieke/prettymapp
Sep 2021 - Dec 2022
🖼️ Create beautiful maps from OpenStreetMap data in a streamlit webapp
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:5 releases, 1 review, 183 commits in 1 year 2 months
Contributions summary:Christoph's contributions primarily focused on implementing and testing the functionality of the `prettymapp` application. They added new features, such as getting the area of interest (AOI) based on user input and querying OpenStreetMap (OSM) data. They also refactored code related to handling map projections. Furthermore, they added tests and made changes to adjust street geometries and adjust colors and added export configurations.
openstreetmapopenstreetmap-dataartgeographycartography
marceloprates/prettymaps
Aug 2021 - Aug 2021
A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.
Role in this project:Software Engineer (focus on library development and maintenance)
Software Engineer (focus on library development and maintenance)Contributions:13 commits, 7 PRs, 1 comment in 2 days
Contributions summary:Christoph primarily contributed to the `prettymaps` library, demonstrating a focus on code cleanup, refactoring, and improving the library's functionality. Their work included fixing a Coordinate Reference System (CRS) issue, refactoring code for clarity and efficiency, adjusting the setup for the library, adding a descriptive text, and excluding unnecessary folders. Furthermore, the user optimized the code by implementing shapely.geometry.box and applying code formatting using Black.
openstreetmap-dataosmnxshapelypythongenerative-art
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