Job Description: Senior Quantitative Researcher
Position Overview
We are seeking a highly skilled and experienced Senior Quantitative Researcher to join our dynamic team. The ideal candidate will possess a strong background in computational and applied mathematics, with a proven track record of developing innovative algorithms and quantitative models in the financial industry. This role involves conducting advanced research, designing and implementing quantitative strategies, and collaborating with cross-functional teams to drive business decisions.
Key Responsibilities
- Develop and optimize quantitative models and algorithms for pricing, risk management, and trading strategies.
- Conduct research on time-series analysis, stochastic processes, PDE-constrained optimization, and statistical methods.
- Implement high-performance computational solutions using programming languages such as C++ and MATLAB.
- Apply machine learning and data mining techniques to extract insights from large datasets.
- Collaborate with other researchers and stakeholders to present findings and recommend data-driven strategies.
- Enhance existing models through variance reduction techniques, parallel computing, and algorithmic improvements.
- Stay updated with academic and industry advancements in quantitative finance and integrate relevant innovations into practice.
Qualifications
- Ph.D. in Computational and Applied Mathematics, Mathematics, Financial Engineering, or a related field.
- 5+ years of experience in quantitative research within the financial sector.
- Strong proficiency in C++, MATLAB, and experience with parallel computing (e.g., MPI).
- Solid understanding of stochastic calculus, numerical methods, optimization, and Bayesian inference.
- Experience with Monte Carlo methods, Kalman filtering, PCA, and other statistical techniques.
- Demonstrated ability to develop and implement efficient algorithms for large-scale problems.
- Excellent communication skills with the ability to present complex ideas clearly and effectively.
- Proven record of academic and professional achievements in quantitative research.
Preferred Skills
- Experience with adjoint-based methods and inverse problems.
- Knowledge of financial derivatives pricing and energy markets.
- Familiarity with data assimilation techniques and machine learning applications in finance.
- Publications or contributions to open-source projects in relevant fields.
What We Offer
- Competitive compensation and benefits package.
- Opportunities for professional growth and collaboration with leading experts.
- A stimulating environment that encourages innovation and continuous learning.