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Quantitative Researcher, Algorithmic Trading, Machine Learning
Quantitative researcher with experience in alpha and execution research using statistical and machine learning methods. Asset classes covered are fixed income, FX and equities. - Trading idea generation and backtesting - Market microstructure & execution research - PhD in Computational Finance & Machine Learning from University College London. Technical skills: Machine learning, Financial econometrics, Statistics, Economics Advanced: Python, Julia, Matlab; Basic: kdb+/q, SQL, VBA, C/C++, R Bilingual in English and Thai, elementary proficiency in French
UCL
Doctor of Philosophy (PhD), Computational Finance & Machine Learning
January 1, 2013 – January 1, 2017
Drucker School of Management
Master of Science, Financial Engineering
January 1, 2006 – January 1, 2008
McGill University
Bachelor of Commerce, Finance and Economics
January 1, 2002 – January 1, 2006
Barclays Investment Bank
Quantitative Researcher, Rates Systematic Market Making
June 1, 2021 – August 1, 2024
State Street
VP Quantitative Researcher - Machine Learning
October 1, 2017 – June 1, 2021
London, United Kingdom
Jetstone Asset Management
Quantitative Researcher (contract)
May 1, 2017 – September 1, 2017
London, United Kingdom
UCL
PhD Researcher in Computer Science
January 1, 2013 – January 1, 2017
London, United Kingdom
The Wharton School, University of Pennsylvania
Visiting Scholar
January 1, 2012 – January 1, 2012
Greater Philadelphia Area
Thammasat Business School, Thammasat University
Lecturer in Finance (with tenure)
January 1, 2008 – January 1, 2013
Bangkok Metropolitan Area, Thailand
Cultural Fit Analysis
The candidate's background is heavily concentrated in quantitative finance and academic research, indicating a strong fit for data-intensive, analytical environments. The diversity of roles from lecturer to quantitative researcher in investment banks and asset management firms suggests adaptability to different organizational structures within the financial sector. The target role of 'Data Analyst' aligns well with the candidate's demonstrated skills in data collection, cleaning, prediction, and model building, particularly within financial contexts.
Soft Skills & Operational Fit
The candidate's extensive experience in leading research and developing complex models suggests strong problem-solving, analytical thinking, and independent work capabilities. The descriptions imply a detail-oriented and results-driven approach. However, specific soft skill assessments (e.g., teamwork, communication style) are not available from the provided data.