Quant & Data Science

Quant Trader - Crypto - HFT

Quant Trader - Crypto - HFT

  • Location

    London

  • Sector:

    Quant & Data Science

  • Job type:

    Permanent

  • Salary:

    £250000 - £350000 per annum + Bonus and Options

  • Contact:

    Holly Horton

  • Contact email:

    hhorton@vertuspartners.com

  • Job ref:

    QT/HH/3108_1693474026

  • Published:

    10 months ago

  • Expiry date:

    2023-09-30

  • Startdate:

    ASAP

  • Consultant:

    ConsultantDrop

Quant Trader - Crypto - HFT

As a Quantitative Trader, you will be an integral part of the trading team, responsible for evaluating, refining, and developing high-performing HFT trading strategies. Your role will involve a combination of strategy review, enhancement, and new strategy creation, using your strong analytical skills to ensure the trading activities remain at the forefront of the industry.

Key Responsibilities:

  • Review and analyse existing HFT trading strategies to identify areas for improvement and optimization.
  • Collaborate with Trading Engineers to implement and execute strategies effectively, leveraging your expertise in C++.
  • Design and develop new trading strategies based on market insights, data analysis, and quantitative research.
  • Stay up-to-date with the latest trends and developments in the crypto market to ensure our strategies remain competitive.
  • Work closely with the wider trading team to contribute to the overall success of our trading operations.

Requirements:

  • Proficiency in C++ is essential, as you will be actively involved in implementing trading strategies.
  • Prior experience in crypto trading is highly desirable, but candidates with a strong background in FX trading from a bank will also be considered.
  • A deep understanding of financial markets, trading principles, and quantitative analysis.
  • Strong problem-solving skills and the ability to work under pressure in a fast-paced environment.
  • Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
  • A degree in a relevant quantitative field (e.g., mathematics, finance, computer science) is a plus.