Job Description
Are you ready to redefine the future of algorithmic trading? Apex Global Capital is seeking a highly analytical and driven Senior Financial Quantitative Analyst to join our elite team in the heart of New York City. You will be responsible for developing sophisticated pricing models, managing risk exposure, and leveraging massive datasets to gain a competitive edge in volatile markets.
We offer a dynamic, high-stakes environment where innovation is not just encouraged—it is demanded. You will work alongside world-class data scientists and financial strategists to build the next generation of financial products.
Responsibilities
- Develop, test, and implement advanced mathematical models for pricing derivatives and structured products.
- Analyze large-scale financial datasets to identify market inefficiencies and trading opportunities.
- Collaborate with engineering teams to integrate quantitative strategies into our high-frequency trading platforms.
- Perform rigorous backtesting of trading algorithms to ensure robustness and capital protection.
- Provide actionable insights and quantitative research to executive leadership for strategic decision-making.
- Monitor model performance and adjust parameters in real-time to mitigate market risk.
- Mentor junior analysts on best practices for statistical modeling and computational finance.
Qualifications
- Master’s degree or PhD in Financial Engineering, Quantitative Finance, Mathematics, or a related field.
- Minimum of 5 years of experience in quantitative finance or algorithmic trading within a Tier-1 financial institution.
- Exceptional proficiency in Python, C++, or R for financial modeling and data analysis.
- Strong understanding of stochastic calculus, time-series analysis, and econometrics.
- Proven ability to bridge the gap between complex theoretical finance and practical market implementation.
- Demonstrated experience working with cloud-based data environments (AWS/Azure) and SQL.
- Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.