Associate, Model Risk
@ Goldman Sachs

New York, NY
$160,000
On Site
Full Time
Posted 22 days ago

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Job Details

Job Overview

The Associate, Model Risk at Goldman Sachs is responsible for independently validating complex equity pricing models. The role requires rigorous assessment of model assumptions, derivations, programming implementations, and regulatory compliance.

Key Responsibilities

  • Validate mathematical, statistical, and conceptual correctness of models.
  • Review and test programming implementations via code review, unit testing, and integration testing.
  • Develop benchmark models using Monte Carlo simulation, finite difference methods, and tree-based methods.
  • Document validation work in Latex for automated version control.
  • Monitor model performance and investigate major model-related incidents.
  • Collaborate with stakeholders and advise senior management on model risks.

Job Requirements

Applicants must have a Master’s degree in Mathematics, Finance, Financial Engineering, Physics, Computer Science, or a related field with one year of experience; or a Bachelor’s degree with three years of relevant experience. Proficiency in Python, R, MATLAB, C++/Java, SQL, Latex, and numerical techniques including Monte Carlo simulation is required.

Compensation

The annual base salary ranges between $137,000 and $180,000.

Key skills/competency

  • Model Validation
  • Equity Pricing
  • Monte Carlo
  • Finite Differences
  • Code Review
  • Unit Testing
  • Integration Testing
  • Latex Documentation
  • Regulatory Compliance
  • Risk Analysis
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How to Get Hired at Goldman Sachs

🎯 Tips for Getting Hired

  • Research Goldman Sachs culture: Explore mission, values, and recent news.
  • Customize your resume: Highlight model validation and testing expertise.
  • Showcase technical skills: Emphasize Python, C++, and SQL proficiency.
  • Prepare for interviews: Review regulatory compliance and risk management.

📝 Interview Preparation Advice

Technical Preparation

Review Python and C++ coding basics
Practice Monte Carlo simulation techniques
Study numerical methods and finite differences
Refine unit and integration testing skills

Behavioral Questions

Describe effective stakeholder communication.
Explain handling of regulatory compliance issues.
Discuss teamwork during model incidents.
Outline problem resolution under pressure.

Frequently Asked Questions