In recent years, quantitative recruiting has seen firms implement stricter screening processes and elevate talent requirements. In practice, several new trends have emerged, notably a surge in demand for C++ expertise.
Through this article, you will learn:
- Why C++?
- Where Python fits in.
- Compensation levels for quantitative C++ roles.
1. C++ vs. Python
While both C++ and Python are used in quantitative trading system development, experience demonstrates that systems built with C++ achieve significantly superior execution speeds.
Speed is paramount in quantitative trading, particularly for high-frequency trading (HFT). Consequently, quantitative firms show a strong preference for candidates with deep C++ proficiency for system development roles.
Python's strength lies in its relative simplicity and its powerful ecosystem of high-performance libraries like NumPy, Pandas, and SciPy. These libraries facilitate complex statistical analysis, numerical computation, and data processing.
Therefore, for roles focused on developing machine learning platforms, candidates specializing in Python hold a distinct advantage.
2. Exceptionally Lucrative C++ Compensation
C++ engineers are exceptionally well-compensated, with the acute talent shortage continually driving compensation higher. The packages offered by quantitative trading firms are particularly remarkable.
Surveys indicate that the average total compensation for C++ engineers with 4-8 years of experience in the United States reaches $960,000. Concurrently, the widespread application of machine learning in quantitative trading is also boosting salaries for professionals skilled in Python.
Based on hiring data available to AlphaMaker, domestic quantitative firms in China currently offer senior developers compensation packages ranging from RMB 500,000 to 800,000.
3. Why Market Makers Want C++
As noted, quantitative firms typically utilize Python for developing machine learning platforms to build trading models from vast datasets, while C++ is the language of choice for constructing ultra-low-latency execution systems.
Market makers are key institutional participants in financial markets. Their core function is to provide liquidity for underlying instruments, thereby facilitating trading activity.
Operationally, this demands ultra-low-latency execution to ensure fills and to arbitrage informational disparities across the market, thereby managing the inherent risks of market making.
In quantitative market making, strategies often span hundreds or thousands of instruments. Managing such diverse portfolios makes developing low-latency trading systems a necessity, which naturally translates into substantial demand for C++ developers.
Welcome to our Blog!
If you are interested in career opportunities, please send your CV to: recruiter@alphamaker.link
If you would like to share your story, please contact us on WeChat: AMQuantcareer