Required Qualifications: PhD in Physics, Statistics, Mathematics, Operations Research, or a related quantitative field plus 1 year of experience in the job offered or in a related quantitative analytics role.
Specific skills required:
• Strong foundation in quantitative finance, statistics, probability theory, and linear algebra, with demonstrated application to securities pricing, risk modeling, and portfolio analytics.
• Extensive hands-on programming experience in C++ and Python for the development of performance sensitive quantitative models.
• In depth knowledge of financial markets and instruments, including equities, fixed income securities, derivatives (options, futures, swaps), and structured products.
• Demonstrated experience in quantitative modeling for financial markets, including the development, implementation, and validation of pricing models (e.g., Black Scholes, binomial tree methods, Monte Carlo simulation) and risk measurement frameworks.
• Experience applying time series analysis, regression techniques, and statistical inference to complex market data.
• Proficiency in SQL and relational database systems for extracting, manipulating, and analyzing large scale financial datasets.
• Ability to translate quantitative analyses into clear, actionable insights for trading, risk management, and senior stakeholders.
• Familiarity with version control systems (e.g., Git) and collaborative software development practices in a quantitative research environment.