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Quantitative Engineering Associate
2 months ago
Position Overview:
We are seeking an Associate in Quantitative Engineering to join our team at Goldman Sachs & Co. LLC. This role is pivotal in enhancing our financial modeling capabilities and requires a strong analytical mindset.
The successful candidate will be responsible for developing, implementing, and documenting scenarios that encompass a wide array of economic and financial variables relevant to our operations.
Key responsibilities include collaborating with internal teams to assess user requirements from a scenario design viewpoint, while also addressing challenges related to data, modeling, and execution.
Additionally, the role involves analyzing extensive data sets, both structured and unstructured, to construct predictive models that inform business-critical market variables. The candidate will refine and enhance scenarios by applying expertise in financial markets, economic trends, statistical analysis, and programming techniques.
Another critical aspect of this position is the development and evaluation of risk models, identifying and quantifying vulnerabilities across various risk domains, including market, credit, and liquidity risks. The Associate will also be tasked with creating and maintaining comprehensive technical documentation regarding the performance testing of risk models.
Qualifications:
The ideal candidate will possess a Master's degree (or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Applied Mathematics, or a related quantitative discipline, along with one (1) year of relevant experience in a similar role. Alternatively, a Bachelor's degree (or foreign equivalent) in the aforementioned fields with three (3) years of experience will also be considered.
Essential skills include proficiency in C++, Java, or Python; experience in developing probability and pricing models based on financial mathematics principles such as stochastic calculus and no-arbitrage pricing theory; and expertise in quantitative analysis and model development utilizing advanced econometric, statistical, and mathematical techniques.
Furthermore, candidates should have experience in risk management or scenario-based analysis, developing quantitative risk analytics, and creating robust data management and analysis tools to support investment processes. Familiarity with statistical performance analysis techniques, including Linear Regression and Time Series Analysis, is also required.
The Goldman Sachs Group, Inc. is an equal opportunity employer, committed to diversity and inclusion in the workplace.
