Maarten Scholl
Research Scientist at INET-Complexity
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolMaarten Scholl is a research scientist with a decade of experience applying machine learning and agent-based modelling to financial markets, completing a DPhil in Computer Science at the University of Oxford. His work spans deep factor models, GANs and market ecology, with industry-facing research stints at J.P. Morgan and the European Central Bank where he analysed regulatory trade data to inform policy and stress-testing. Comfortable straddling academia and practice, he has built distributed computational frameworks for finance and contributed to projects in synchronised graph computation and exposure management. Based in Amsterdam, he brings a rare combination of hands-on engineering, quantitative finance expertise and interdisciplinary curiosity—his background even includes 3D asset development and game tooling—making him adept at translating complex models into actionable insights.
10 years of coding experience
1 year of employment as a software developer
MSc Computational Science, Computational Finance, 9, MSc Computational Science, Computational Finance, 9 at VU University AmsterdamDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of OxfordBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Universiteit UtrechtMSc Computational Science, Computational Finance, 9, MSc Computational Science, Computational Finance, 9 at University of AmsterdamBachelor's Degree, Information Science, Bachelor's Degree, Information Science at Utrecht University
English, Dutch, German
Github Skills (56)
simulation10
iteration10
financial10
parallel10
computation10
routines10
finance10
agent-based-modeling10
sampling10
economics10
datasets10
distributed-computing10
agent10
calibration10
financial-markets10
Programming languages (4)
Github contributions (5)
INET-Complexity/market-ecology
Dec 2020 - Oct 2021
Contributions:1 release, 235 commits, 107 pushes in 11 months
INET-Complexity/ESL
Jul 2019 - Jun 2022
The Economic Simulation Library provides an extensive collection of tools to develop, test, analyse and calibrate economic and financial agent-based models. The library is designed to take advantage of different computer architectures. In order to facilitate rapid iteration during model development the library can use parallel computation. Economic models developed using the library can be deployed into large-scale distributed computing environments when working with large model instances and datasets and provides routines to set up large-scale sampling computations during the analysis and calibration process.
Contributions:63 releases, 906 commits, 10 PRs in 2 years 11 months
calibration-processsimulationsimulation-libraryfinancial-marketsfinance
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