Data Science Quantitative Engineer for Digital Transaction Banking
3 weeks ago
About the Role
We are seeking a highly skilled Data Science Quantitative Engineer to join our team in Bengaluru, India. As a key member of our global quant team, you will be responsible for all modeling aspects of Transaction Banking (TxB), including portfolio management, pricing, risk monitoring, funding optimizations, fraud detection, and innovative analytics & reporting across products in TxB.
Key Responsibilities
- Build pricing models for liquidity and other banking products under various market conditions.
- Perform historical data analysis to accurately model client behaviors, including liquidity outflows and funding optimizations.
- Design proper portfolio management and hedging strategies against various different market risk, including IR and FX risk.
- Build advanced end-to-end machine learning models for fraud detection including data pipeline, feature engineering and full model implementation.
- Develop scalable production quality code to implement and deploy to production environment.
- Accurately document the modeling assumptions and methodologies, and work with Model Risk team through model validations.
- Build internal analytics/ dashboards for monitoring portfolio risk and providing insights to leadership team.
- Interact closely with product/finance/risk teams to ensure smooth cross-team collaborations.
Requirements
- BS/MS or PhD in a quantitative field – Mathematics, Statistics, Mathematical Finance/Financial Engineering, other Engineering.
- 3+ Years of experience in Mathematical Finance domain.
- Quantitative background including an understanding of probability and statistics.
- Strong programming background in compiled or scripting languages (Python, R, Java, etc.).
- Ability to explain complex models and analysis to diverse audience.
Preferred Qualifications
- Knowledge of Tradable/SecDB/Slang is a strong plus.
- Experience in other transaction banking/corporate deposit modeling/treasury function as a quant is preferred.
- Interest rate/liquidity risk modeling or other similar financial modeling experience is a plus.
- Familiarity with object-oriented coding languages and production quality code development.
About Us
At Goldman Sachs, we commit our people, capital, and ideas to help our clients, shareholders, and communities grow. We believe who you are makes you better at what you do. Our compensation package includes an estimated salary of ₹18,00,000 - ₹25,00,000 per annum, depending on experience and qualifications.
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