Goldman Sachs's Model Risk Management (MRM) team is looking to ensure the safety and soundness of the firm's models, including AI and machine learning models, by validating their performance, accuracy, and reliability.
Requirements
- Programming expertise in Python, including experience with relevant data science libraries (e.g., NumPy, Pandas, TensorFlow, Pytorch).
- Relevant experience working with statistical modelling, machine learning algorithms or natural language processing.
- Experience with AI models, including machine learning and deep learning
- Familiarity with model validation and testing methodologies
Responsibilities
- Independently validate the performance, accuracy, and reliability of AI models used within Goldman Sachs, focusing on aspects such as accuracy, explainability, model design, and algorithmic robustness.
- Develop and implement validation methodologies and benchmark models tailored to the specific characteristics of AI models.
- Conduct thorough testing and analysis of model outputs, identifying and documenting potential risks and limitations.
- Collaborate with model developers and business stakeholders to address identified issues and improve model performance.
Other
- A Bachelor, Master or Ph.D. degree in Computer Science, Mathematics, Physics, Engineering, or a closely related quantitative field.
- Excellent analytical, problem-solving, and communication skills.
- Demonstrated curiosity, ownership, and a willingness to work in a collaborative environment.
- Ability to work in a fast-paced environment and adapt to changing priorities
