Job Description
Are you a sharp, analytical mind looking to redefine quantitative strategies in the heart of Wall Street? Apex Global Capital is seeking a Senior Quantitative Financial Analyst to join our elite trading research division. In this role, you will bridge the gap between complex mathematical modeling and high-frequency execution strategies, leveraging cutting-edge machine learning and predictive analytics to drive alpha generation.
We offer a collaborative, high-octane environment where your intellectual curiosity is rewarded, and your models directly impact global portfolios. If you thrive on solving complex, multi-dimensional financial puzzles and want to work alongside industry-leading quantitative researchers, this is your next career-defining move.
Responsibilities
- Design, backtest, and implement systematic trading models and quantitative strategies across global asset classes.
- Analyze large, unstructured alternative datasets to identify market inefficiencies and predictive alpha signals.
- Collaborate closely with data engineering teams to build and optimize robust data pipelines and production-grade execution systems.
- Monitor real-time portfolio risk metrics and optimize execution algorithms to minimize transaction costs and market impact.
- Present quantitative research findings, model performance metrics, and risk-adjusted return profiles to senior investment committees.
- Maintain and continuously refine existing statistical arbitrage and machine learning models to adapt to evolving market regimes.
Qualifications
- Master’s or Ph.D. in Quantitative Finance, Mathematics, Statistics, Physics, Computer Science, or a closely related STEM field.
- Minimum of 3-5 years of hands-on experience as a Quantitative Analyst or Researcher at a hedge fund, asset manager, or investment bank.
- Expert-level proficiency in Python (including Pandas, NumPy, Scikit-Learn) and robust experience with SQL and C++.
- Deep theoretical and practical understanding of time-series analysis, statistical modeling, and machine learning techniques.
- Proven track record of building and validating portfolio optimization and multi-factor risk models.
- Exceptional communication skills, with a proven ability to articulate complex mathematical concepts to non-technical stakeholders.