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Quantitative Risk Modeler

2 months ago

Bengaluru, Karnataka, India Goldman Sachs Full time

Who We Are

At Goldman Sachs, our Engineers don’t just make things – they make things possible. Change the world by connecting people and capital with ideas. We are looking for talented Quantitative Risk Modelers to join our team and help us build a modern and digital-first transaction banking solution. Our goal is to provide a best-in-class digital product that helps clients to succeed by giving them a holistic view of their business.

About The Team

As part of our global quant team, you will be responsible for all modeling aspects of Transaction Banking, including portfolio management, pricing, risk monitoring, funding optimizations, fraud detection, as well as innovative analytics & reporting across products in Transaction Banking. You will be leveraging various quantitative and statistical/machine learning methods to come up with solutions that are accurate, robust and scalable.

Responsibilities

  1. Build pricing models for liquidity and other banking products under various market conditions.
  2. Perform historical data analysis to accurately model client behaviors, including liquidity outflows and funding optimizations.
  3. Design proper portfolio management and hedging strategies against various different market risk, including IR and FX risk.
  4. Build advanced end-to-end machine learning models for fraud detection including data pipeline, feature engineering and full model implementation.
  5. Develop scalable production quality code to implement and deploy to production environment.
  6. Accurately document the modeling assumptions and methodologies, and work with Model Risk team through model validations.
  7. Build internal analytics/ dashboards for monitoring portfolio risk and providing insights to leadership team.
  8. Interact closely with product/finance/risk teams to ensure smooth cross-team collaborations.

BASIC QUALIFICATIONS

  1. BS/MS or PhD in a quantitative field – Mathematics, Statistics, Mathematical Finance/Financial Engineering, other Engineering.
  2. 3+ Years of experience in Mathematical Finance domain.
  3. Quantitative background including an understanding of probability and statistics.
  4. Strong programming background in compiled or scripting languages (Python, R, Java, etc.).
  5. Ability to explain complex models and analysis to diverse audience.

About Goldman Sachs

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. We believe who you are makes you better at what you do. We’re committed to fostering and advancing diversity and inclusion in our own workplace and beyond.