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Kevin Thomas Webster, PhD


D.E. Shaw | Quantitative Researcher

Nov 2023 - Present

Garden Leave | Author, Researcher, Teacher

Oct 2021 – Oct 2023

Citadel | Quantitative Researcher

Feb 2016 – Oct 2021

Deutsche Bank | Quantitative Researcher

May 2014 – Feb 2016

BNP Paribas | Research Intern

Apr 2010 – Aug 2010


Academic Teaching

Fordham University | Adjunct Professor

Aug 2023 - Oct 2023


Columbia University | Adjunct Assistant Professor

Jan 2023 - Oct 2023

Imperial College LondonVisiting Assistant Professor (Reader)

Aug 2022 - Oct 2023

Princeton UniversityVisiting Lecturer 

Jan 2016 - Jul 2016


Princeton University | PhD in Operations Research and Financial Engineering

Sep 2010 - May 2014

Ecole Polytechnique | Bachelor’s and Master’s degrees in Mathematics and Applied Mathematics

Sep 2007 - May 2010


With a deep passion for data analysis and a profound appreciation for the power of quantitative methods to uncover insights in finance, I am devoted to unlocking the potential of mathematical tools to solve real-world problems.


I am an award-winning quant with ten years of experience building large-scale, systematic, and model-driven frameworks for trading. I have deployed algorithms for top-tier financial institutions such as D.E. Shaw, Citadel, Deutsche Bank, and BNP Paribas. My projects include:


  • Alpha research at all frequencies.

  • Price impact modeling for sizable portfolios.

  • Market-making.

  • Portfolio construction.


I collaborate with the industry's brightest traders, technologists, and portfolio managers, thriving in medium-sized quantitative teams emphasizing learning, live trading, and tool-building. From an implementation perspective, I take a comprehensive, strategic, and action-focused approach to every product I build. From a modeling perspective, I tilt toward high-dimensional statistics, emphasizing tools for team members to understand and communicate the insights gained from models. From a leadership perspective, I focus on the crucial question "What is my team's edge?" and streamline, communicate, and refine that edge to maximize the team's value.

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