Global Banking & Markets-New York-Associate, Quantitative Engineering-10452362

Associate, Quantitative Engineering

Location: New York, New York

Responsibilities

• Develop, implement, and document scenarios comprised of a broad range of economic and financial variables for businesses within the Firm.
• Collaborate with internal stakeholders to analyze user needs from a scenario design perspective and address data, model, and implementation issues.
• Analyze large datasets (structured and unstructured) to build predictive models of business-relevant market variables.
• Develop, refine, and improve scenarios using expertise in financial markets, economics, current events, statistical analysis, and programming.
• Build and challenge risk models, identifying and quantifying vulnerabilities across market, credit, and liquidity risk and modeling.
• Create and maintain clear and complete technical documentation of risk-model performance testing approaches and processes.

Requirements

Education and Experience: Master’s degree (U.S. or foreign equivalent) in Financial Engineering, Financial Economics, Applied Mathematics, Data Science, Operations Research, or a related field with one (1) year of experience in the job offered or a related quantitative engineering role; or Bachelor’s degree (U.S. or foreign equivalent) in the same fields with two (2) years of experience in the job offered or a related quantitative engineering role.

Prior experience must include: With a Master’s degree, one (1) year of experience; with a Bachelor’s degree, two (2) years of experience, including at least 5 of the 7 following skills:

• C++, Java, or Python.
• Developing probability and pricing models using financial mathematics principles, including stochastic calculus, no-arbitrage pricing theory, partial differential equations, multivariable calculus, linear algebra, numerical methods, optimization, probability, or random processes.
• Quantitative analysis and model development using advanced econometric, statistical, and mathematical techniques, including Bayesian analysis, time series analysis, or machine learning algorithms.
• Performing risk management or scenario-based analysis.
• Developing quantitative risk analytics, including factor models.
• Developing rigorous and scalable data management and analysis tools to provide risk oversight and support the investment process.
• Statistics and data-driven performance analysis, including Linear Regression or Time Series Analysis to measure performance.

Salary Range

Annual base salary: $150,000 - $189,000