p>Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra) Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques Numerical methods and optimization, Monte Carlo simulation and finite difference techniques Risk management methods (value-at-risk, expected shortfall, stress testing, backtesting, scenario analysis) Financial products knowledge: seasoned level in understanding of markets and financial derivatives in equities, interest rate, and commodity products Seasoned level in programming skills Advanced proficiency in using a programming language (e.g., Java, C++, Python, R, MATLAB, etc.) in a collaborative software development setting. NAG, MATLAB) Experience with automated testing frameworks (e.g., Junit, TestNG, PyTest, etc.) Experience with CI/CD and DevOps tools (e.g., Git, GitHub and various profiling and telemetry tools) is required for model implementation and application development Experience with high performance computing, distributed computation engines and cloud computing Seasoned level in office technology such as PowerPoint, Confluence, Latex, Word, and Excel.