Overview

As Algorithmic Credit Trader at Santander CIB, you will design and run in-house data infrastructure and systematic trading strategies across credit products. You will manage two-sided market-making for DM and EM credits and develop multi-factor models to generate alpha. You’ll integrate diverse data sources, build pricing and risk tools, and monitor execution quality across electronic and voice channels. This role combines advanced analytics, trading, and cross-functional collaboration to drive scalable, data-driven credit trading at a leading global bank.

Compensaciones / Incentivos

- hybrid working model
- competitive salary with performance bonuses
- BeHealthy wellness program
- childcare support
- educational opportunities (SantanderOpen Academy)
- gym/WellHub membership, meal subsidy, parking, shuttle service

Responsabilidades

- Design, build, and maintain data infrastructure supporting systematic credit trading
- Develop and deploy algorithmic trading strategies across cash bonds, CDS, indices, ETFs
- Establish a two-sided algorithmic market-making and trading book across DM and EM credit markets
- Create multi-factor quantitative models to identify trading opportunities and alpha
- Integrate alternative datasets, microstructure signals, liquidity metrics, and fundamental indicators into models
- Build pricing engines, risk management frameworks, portfolio analytics, and execution tools
- Monitor execution quality, transaction costs, and trading performance across channels




- Develop risk analytics and portfolio visualization tools to monitor exposures by region, sector, tenor, liquidity
- Collaborate with technology, quant research, data science, and risk management to scale infrastructure
- Support market access initiatives and primary/ETF market activities
- Ensure adherence to regulatory requirements, risk limits, and governance standards

Requisitos principales

- Advanced degree in a quantitative discipline
- Strong experience in systematic/electronic trading, preferably in credit markets
- Deep understanding of fixed income and credit products
- Proven experience developing quantitative models and factor-based strategies
- Strong Python programming skills and experience with large datasets and market data APIs
- Knowledge of statistical modeling, machine learning, and market microstructure
- Experience building pricing engines, risk systems, and trading analytics platforms
- Proven ability to manage large credit risk portfolios and market-making books
- Experience trading/hedging CDS indices, ETFs, and cash bonds
- Knowledge of electronic trading venues and market structure across markets

- Strong communication abilities and collaboration across teams
- Analytical mindset with attention to detail
- Ability to work in a high-pressure trading environment
- Python
- Large datasets, database architectures, market data APIs
- Statistical modeling and machine learning techniques

📌 Algorithmic Credit Trader (Quantitative Credit Trading) (Boadilla del Monte)
🏢 Grupo Santander
📍 Boadilla del Monte