Marco Van Der Linden
Staff Data Scientist
Leiden, South Holland, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolMarco Van Der Linden is a Staff Data Scientist and seasoned software engineer with over a decade of professional ML experience built on nearly two decades of software development in C# and Python. He designs and ships production-ready deep learning systems—particularly in reinforcement learning—while also architecting scalable tech stacks and intuitive UIs that make models actionable for clinicians. At Pacmed he blends hands-on model building with engineering leadership, driving adoption of AI tools and cultivating best practices across teams. Marco contributes to notable open-source ML infrastructure work (e.g., improving DeepChem’s build and Docker processes), showing attention to reliability and reproducibility beyond model code. A natural coach and critical thinker, he consistently challenges assumptions and mentors peers to raise team capability. Based in Leiden, he pairs scientific-software rigor with practical product instincts to deliver impactful, deployable AI solutions.
11 years of coding experience
24 years of employment as a software developer
- Computer Science - SE, - Computer Science - SE at Leiden UniversityVWO, VWO at Groene Hart Lyceum
English, Dutch
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
docker10
deep-learning10
tensorflow10
dockers10
build-automation10
cicd10
python9
drug-discovery8
science7
quantum-chemistry7
Programming languages (8)
Github contributions (5)
deepchem/deepchem
May 2022 - Jun 2022
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Role in this project:
DevOps Engineer
DevOps EngineerContributions:3 reviews, 6 commits, 2 PRs in 1 month
Contributions summary:Marco focused on improving the build process and dependencies within the DeepChem project. They added warnings to model loading, ensuring better error handling. The user addressed the Docker build process, and also added the [tensorflow] dependency to the pip install command in the tutorial notebook. Additionally, the user applied code formatting using yapf, ensuring code consistency.
chemistrysciencedrug-discoverydeep-learningbiology
swb-ief/etl-pipeline
Dec 2020 - Jul 2021
The Covid Lens
Contributions:55 reviews, 236 commits, 72 PRs in 7 months
covdi19lens
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