About machineByte

machineByte, a product of EQDerivatives, is created for investment professionals, who are currently exploring or active in machine learning, AI and alternative data in financial markets.

The Platforms


Join senior machine learning, data science and asset allocation professionals from firms such as GSAM, Citadel, BlackRock, PIMCO, J.P.Morgan Asset Management, World Bank, AXA IM, OPTrust, Neuberger Berman and others at machineByte conferences around the globe. Our educational seminars provide training on Python for finance, natural language processing for portfolio construction and reinforcement learning for investment management, among other topics. Access to presentations and content delivered at machineByte events is only open to machineByte members. 


machineByte’s industry & academic ThinkTanks in London, New York & Hong Kong bring together the leading quantitative, data science and machine learning professionals in finance and tech to discuss the latest trends and innovations in machine learning in finance.

Data & Research

Our unique research and data provides analysis on how institutional investors are applying machine learning across markets, asset classes and products. The research and data also shows where investors are using alternative data and with which providers, where they are looking to grow their application of machine learning and the challenges they face when it comes to areas such as deep learning and big data in portfolio construction, allocation frameworks, trading, portfolio management and analysis/modelling. We also offer bespoke research that will identify non-linear trends through the application of data science techniques in quantitative investing markets. For further information, please email research@machineByte.com.

The Journal of Machine Learning in Finance

machineByte’s journal delivers academic and practitioner insights from quantitative finance, data science and tech innovators with one clear goal: providing a platform that fosters education and innovation in machine learning and alternative data through independent research. For further information, please email journal@machineByte.com. 


machineByte’s podcasts, webinars and video content feature insights from distinguished machine learning and data science professionals on programming, types of learning and generating alpha through machine learning, among other areas.

The Team

We want to hear from you.

For content or all other machineByte platform questions, please contact Chantal Hermans at chantal@machineByte.com in London.

For membership / sponsorship questions, please contact Chas Reese at chas@machinebyte.com in Boston.

To connect with our journalism team, please contact Elinor Comlay at elinor@machinebyte.com

For questions related to our research, please contact Patrick Fay at pat@machinebyte.com.

The Founders

Reach out to co-founders Peter Thompson at peter@machinebyte.com in Chicago or Rob McGlinchey at rob@machinebyte.com in London.