Quantitative Analytics Lead

Key Skills: C++, Python, Quant.

Roles and Responsibilities:

• Collaborate closely with trading desks to develop and enhance pricing and risk management tools on strategic platforms.
• Contribute to the development and optimization of Python-based quantitative tools and C++ libraries used by Front Office Trading, Risk, and Finance teams.
• Lead the implementation of new pricing and risk methodologies, adapting to evolving market and regulatory frameworks such as Libor transition and the Fundamental Review of the Trading Book (FRTB).
• Build and lead a high-performing global Quant team, ensuring delivery excellence and strong ownership of quantitative development initiatives.
• Conduct thorough quantitative investigations, draw data-driven conclusions, and present findings to peers and supervisors for feedback and review.
• Take ownership of SAF (Strategic Analytics Framework) client projects, including front-office intra-day and end-of-day C++ pricing libraries.
• Develop and enhance key modules within the in-house Python library, promoting modularity, reusability, and high code quality.
• Promote and adopt quantitative and software engineering best practices across teams and when collaborating with stakeholders including Front Office Quants, Risk, and Finance departments.

Experience Requirement:

• 10 years of professional experience in quantitative analytics, with at least 6 years of hands-on development in Python and/or C++.
• Strong technical knowledge of multi-asset class trade valuation, risk, and P&L calculations, especially from a front-office perspective.
• Demonstrated experience in pricing derivative products, including a strong understanding of product attributes, cashflows, and present value (PV) calculations.
• Experience developing front-office Quant libraries with in-depth expertise in interest rate derivatives and options pricing models.
• Hands-on experience with market data systems and an understanding of how curves and volatility surfaces are constructed from market quotes.
• Proven experience applying advanced mathematical concepts to quantitative finance problems, including stochastic calculus, numerical methods, optimization, time series analysis, and econometrics.

Education: Any Post Graduation, Any Graduation.

Apply NowShare this Job