Davis Zhang

Quantitative Trader at Eschaton Trading
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Location
Chicago, US

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Credentials

  • Series 57
    FINRA
    Nov, 2019
    - Sep, 2024

Experience

    • United States
    • Capital Markets
    • 1 - 100 Employee
    • Quantitative Trader
      • May 2021 - Present
    • Netherlands
    • Capital Markets
    • 700 & Above Employee
    • Quantitative Trader
      • Sep 2019 - Jul 2020

      - Traded QQQ, NQ, and NDX options in an execution-based role. - Traded ES, NQ, RTY, and YM futures using a high-frequency strategy. Primarily research-based role centered around the development of an algorithmic strategy with minimal trader intervention. - Traded QQQ, NQ, and NDX options in an execution-based role. - Traded ES, NQ, RTY, and YM futures using a high-frequency strategy. Primarily research-based role centered around the development of an algorithmic strategy with minimal trader intervention.

    • Undergraduate Research Assistant
      • Sep 2018 - May 2019
    • United States
    • Hospitals and Health Care
    • 700 & Above Employee
    • Undergraduate Research Assistant
      • Jan 2018 - Oct 2018

      Assisted in a retrospective analysis of RBC transfusion efficacy in critically ill patents over 65 which applied propensity score matching and association rule mining to examine the relationship between RBC transfusion, 30-day mortality, and 1-year mortality rates. Assisted in a retrospective analysis of RBC transfusion efficacy in critically ill patents over 65 which applied propensity score matching and association rule mining to examine the relationship between RBC transfusion, 30-day mortality, and 1-year mortality rates.

    • United Kingdom
    • Environmental Services
    • Software Developer Internship
      • May 2018 - Aug 2018

      Automated core team operations by creating a CI/CD pipeline with Ansible and Jenkins to deploy market data applications to AWS EC2 instances. - Replaced multiple manual processes with Python scripts to automate deployments with improved speed/accuracy - Reduced the time required to test/deploy the team’s application suite from 18 hours to less than 3 hours Automated core team operations by creating a CI/CD pipeline with Ansible and Jenkins to deploy market data applications to AWS EC2 instances. - Replaced multiple manual processes with Python scripts to automate deployments with improved speed/accuracy - Reduced the time required to test/deploy the team’s application suite from 18 hours to less than 3 hours

    • United States
    • Higher Education
    • 700 & Above Employee
    • CS 3650 - Database Management Systems TA
      • Jan 2018 - May 2018

      Provided office hours and graded student assessments, assignments, and projects. Provided office hours and graded student assessments, assignments, and projects.

    • United States
    • Automotive
    • 500 - 600 Employee
    • Data Analysis Intern
      • Jun 2017 - Sep 2017

      Researched and implemented neural network, random forest, and association rule mining strategies to identify cases of dealership fraud for auto companies. - Wrote diagnostic tests to evaluate the performance of in-place models - Met with end clients to determine project requirements and evaluate model performance - Increased accuracy over existing statistical models from 30% to 60% Researched and implemented neural network, random forest, and association rule mining strategies to identify cases of dealership fraud for auto companies. - Wrote diagnostic tests to evaluate the performance of in-place models - Met with end clients to determine project requirements and evaluate model performance - Increased accuracy over existing statistical models from 30% to 60%

Education

  • Vanderbilt University
    Bachelor's degree, Mathematics and Computer Science
    2015 - 2019

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