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Quantitative Developer

Avenir Group

London

On-site

GBP 80,000 - 120,000

Full time

4 days ago
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Job summary

A leading company in investment management is seeking a quantitative developer to optimize trading systems and research tools. This role offers the opportunity to collaborate with experts in a fast-paced environment, significantly impacting the performance of algorithmic trading strategies using C++ and Python.

Benefits

Competitive compensation and benefits
Performance-based incentives
Opportunities to work on cutting-edge technology
Collaborative and research-oriented culture

Qualifications

  • Experience with algorithmic trading systems for at least 5 years.
  • Solid understanding of data structures and algorithms.
  • Ability to work in Linux environment.

Responsibilities

  • Develop and optimise high-performance trading systems in C++ and Python.
  • Enhance and maintain the research and backtesting framework.
  • Work closely with quantitative researchers to build efficient tools.

Skills

Quantitative Trading Logic
C++
Python
High-Performance Computing
Distributed Systems
Data Structures
Algorithim Optimization

Education

Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Engineering

Job description

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As a quantitative developer, you will play a pivotal role in building and optimising our quant trading systems, backtesting infrastructure, and research tools. You will collaborate closely with quantitative researchers, traders, and engineers to translate complex financial models into scalable, low-latency trading solutions.

Key Responsibilities:

  • Develop and optimise high-performance trading systems in C++ and Python for algorithmic trading and execution.
  • Implement, test, and deploy trading strategies based on research-driven insights.
  • Enhance and maintain the research and backtesting framework to support strategy development.
  • Work closely with quantitative researchers to understand their needs and develop efficient tools for data analysis, simulation, and strategy optimisation.
  • Optimise market data pipelines and trade execution engines to improve performance and reduce latency.
  • Ensure system reliability, scalability, and low-latency performance in a fast-paced trading environment.
  • Utilise distributed computing and high-performance computing techniques to enhance algorithmic execution.
  • Integrate with exchange APIs (REST/WebSocket/FIX) for real-time data processing and trading execution.

Required Qualifications:

  • Strong understanding of quant trading logic, market structure, and execution strategies.
  • Proficiency in C++ and Python, with experience in high-performance computing, multi-threading, and distributed systems.
  • Experience with algorithmic trading systems in crypto, equities, FX, or derivatives at least 5 years.
  • Knowledge of financial markets, risk management, and portfolio optimisation.
  • Solid understanding of data structures, algorithms, and software architecture for building robust, scalable systems.
  • Experience working in a Linux environment, including scripting and automation.
  • Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Engineering, or related fields.

Preferred Qualifications:

  • Experience with low-latency trading systems and high-frequency trading (HFT).
  • Background in distributed computing, machine learning, or AI-driven trading models.
  • Familiarity with cloud computing, Kubernetes, or containerised environments.
  • Strong debugging, profiling, and performance optimisation skills.

What We Offer:

  • Competitive compensation and benefits, including performance-based incentives.
  • A fast-paced, innovation-driven environment in the crypto and digital asset space.
  • Opportunities to work on cutting-edge trading strategies and technology.
  • A highly collaborative and research-orientated culture.
Seniority level
  • Seniority level
    Mid-Senior level
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Engineering and Finance
  • Industries
    Investment Management

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