Goldman Sachs is looking to solve risk management problems through robust metrics, data-driven insights, and effective technologies
Requirements
- Programming Languages: Proficiency in Python (preferred) and/or Java/Scala
- ML/AI Frameworks: Familiar with latest LLM, RAG, agentic AI frameworks
- Data Engineering: Strong grasp of data processing pipelines, especially with tools like SNS, SQS, Step Functions, Lambda, RDS
- APIs and Microservices: Proven experience building and consuming RESTful APIs; knowledge of FastAPI or Flask
- Model Deployment: Familiarity with MLOps tools and patterns for deploying, monitoring, and versioning models (e.g., MLflow, SageMaker)
- Cloud Experience: Hands-on with AWS (S3, Lambda, SageMaker, RDS) or equivalent cloud platforms (Azure/GCP)
- Infrastructure as Code: Working knowledge of CI/CD pipelines, Docker, Git, and infrastructure tools like Terraform or AWS CDK
Responsibilities
- developing macroeconomic and financial scenarios for firm-wide scenario-based risk management
- developing and implementing statistical models for credit loss forecasting, business-as-usual risk management and regulatory stress testing requirements
- analyzing large datasets of risk metrics to extract valuable insights about the firm’s exposures
- building and consuming RESTful APIs
- deploying, monitoring, and versioning models using MLOps tools and patterns
- working with data processing pipelines using tools like SNS, SQS, Step Functions, Lambda, RDS
- building and deploying models using cloud platforms like AWS (S3, Lambda, SageMaker, RDS)
Other
- Bachelor's degree or higher in a related field
- Strong traditions of risk management, data analytics and career development opportunities for our people
- We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process
- Ability to work in a challenging, varied and multi-dimensional work environment
- Ability to interface with a variety of divisions around the firm as well as the other regional offices
