Quantitative Researcher – Quant Macro
CW Talent Solutions is partnering with a leading global investment firm to hire a talented Quantitative Researcher focused on macro signals research. This is an exciting opportunity to work at the forefront of systematic investing, developing predictive models across futures and macro asset classes within a dynamic, research-driven environment.
Key Responsibilities:
- Design and develop quantitative signals (alphas) across macro asset classes and futures markets
- Conduct original research using large-scale data sets to uncover market inefficiencies
- Build and backtest models to evaluate signal performance in live trading environments
- Collaborate with other researchers and technologists to integrate signals into systematic strategies
Preferred Experience:
- Bachelor’s, Master’s, or Ph.D. in a quantitative or technical field such as Mathematics, Computer Science, Physics, Electrical Engineering, or Financial Engineering
- Experience in data processing, modeling, and visualization using Python, R, or C++
- Strong academic performance and demonstrated research capabilities
- Interest or experience in macro products (Commodities, FX, Rates, Equity Indices) is a significant advantage
- Independent thinker with a rigorous, methodical approach to problem-solving
- Strong communication skills and a passion for learning about global markets
What’s in it for you?
- Contribute to cutting-edge research at the heart of a globally recognized systematic trading firm
- Join a meritocratic culture that encourages deep thinking, innovation, and continuous improvement
- Exposure to a high-performance environment with robust infrastructure and resources
- Competitive compensation and opportunities for long-term career growth
Why Choose Us?
Our client is a premier quantitative investment firm renowned for its commitment to research excellence and collaborative culture. With a global presence and a focus on data-driven decision making, this is a rare opportunity to shape the future of macro investing through advanced signal research.