Parth Parakh
Quantitative Trader
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolParth Parakh is a quantitative trader based in Amsterdam with a decade of experience applying low-latency pricing models and data-driven strategies across FX and rates markets. He currently drives eFX quantitative efforts at ABN AMRO after building eMacro trading strats at Credit Suisse, where his work spanned FX spot, eNDFs, PMs and UST desks. His background blends rigorous MSc training in Computational Finance from UCL with hands-on software engineering—C++ protocol stack development at Samsung and Python research in speech and financial time-series—bringing both production-grade coding and statistical modeling to trading problems. Past projects include CNN and Bayesian analyses of OpRisk impacts on VaR and implementation of MFCC and DTW speech features, highlighting his versatility across domains. Colleagues describe him as someone who turns complex, low-latency requirements into robust, measurable models and systems. Outside trading desks, he’s comfortable migrating research prototypes into scalable C++/Python implementations, a skill that often accelerates deployment timelines.
10 years of coding experience
3 years of employment as a software developer
Bachelor of Technology (BTech) Electrical and Electronics Engineering, Bachelor of Technology (BTech) Electrical and Electronics Engineering at Indian Institute Of Information Technology Allahabad High School Diploma, High School Diploma at Birla Vidya NiketanUniversity College London
Sanskrit, Hindi, English
Github Skills (3)
python2
financial2
machine-learning1
Programming languages (2)
Github contributions (5)
Parth7/ML-for-finance
Jan 2021 - Sep 2021
Contributions:74 commits, 72 pushes, 1 branch in 7 months
Parth7/CPP-codes
Dec 2015 - Jun 2023
Contributions:36 pushes, 1 branch in 7 years 7 months
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