Goldman Sachs is looking to solve risk management problems by providing robust metrics, data-driven insights, and effective technologies for risk management.
Requirements
- Proficiency in Python (preferred) and/or Java/Scala
- Familiarity with SQL for data manipulation
- Familiar with latest LLM, RAG, agentic AI frameworks
- Strong grasp of data processing pipelines, especially with tools like SNS, SQS, Step Functions, Lambda, RDS
- Proven experience building and consuming RESTful APIs; knowledge of FastAPI or Flask
- Familiarity with MLOps tools and patterns for deploying, monitoring, and versioning models (e.g., MLflow, SageMaker)
- Hands-on with AWS (S3, Lambda, SageMaker, RDS) or equivalent cloud platforms (Azure/GCP)
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
- interface with a wide array of divisional, finance and risk management groups across the firm
- building and consuming RESTful APIs
- deploying, monitoring, and versioning models
- working with structured and unstructured financial data
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
- Commercial awareness and ability to balance control and risk management with commercial responsibilities
- Ability to work in a challenging, varied and multi-dimensional work environment
