Risk, AI Model Validation, Associate, Birmingham

Goldman Sachs; West Midlands; On-site; GBP 60,000 - 90,000; Full time

Job summary

Goldman Sachs is seeking to enhance its Model Risk Management (MRM) team with a focus on validating AI models. The successful candidate will independently validate models, ensuring their accuracy and reliability, while collaborating with developers and stakeholders to enhance model performance.

Qualifications include a degree in a quantitative field, programming expertise in Python, and a solid understanding of statistical modeling and machine learning algorithms. Candidates must exhibit strong analytical and communication skills.

Qualifications

• A degree in a closely related quantitative field is required.
• Expertise in Python programming is essential.
• Understanding of statistical modeling and machine learning algorithms is necessary.
• Candidates should possess strong analytical and problem-solving skills.
• Excellent communication skills are crucial.

Responsibilities

• Validate performance, accuracy, and reliability of AI models.
• Develop and implement validation methodologies for AI models.
• Conduct testing and analysis of model outputs.
• Collaborate with model developers and stakeholders to improve performance.

Skills

Programming expertise in Python

Statistical modelling understanding

Machine learning algorithms understanding

Excellent analytical skills

Problem-solving skills

Communication skills

Education

Bachelor, Master or Ph.D. in Computer Science, Mathematics, Physics, Engineering

Tools

NumPy

Pandas

TensorFlow

Pytorch

Job description

Goldman Sachs's Model Risk Management (MRM) team plays a critical role in ensuring the safety and soundness of the firm's models. MRM validates a diverse set of models, including AI and machine learning models, used within the firm. This role offers the opportunity to make significant contributions to the firm's overall model risk management framework and AI.

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.

Preferred Qualifications

• A Bachelor, Master or Ph.D. degree in Computer Science, Mathematics, Physics, Engineering, or a closely related quantitative field.
• Programming expertise in Python, including experience with relevant data science libraries (e.g., NumPy, Pandas, TensorFlow, Pytorch).
• Understanding of statistical modelling and machine learning algorithms.
• Excellent analytical, problem‑solving, and communication skills.
• Demonstrated curiosity, ownership, and a willingness to work in a collaborative environment.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

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