OverviewAs 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 integral bank.
Compensaciones / Beneficioshybrid working model
competitive salary with performance bonuses
BeHealthy wellness program
childcare support
educational opportunities (SantanderOpen Academy)
gym/WellHub membership, meal subsidy, parking, shuttle service
ResponsabilidadesDesign, 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 principalesAdvanced 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 (Boadilla del Monte)
🏢 Grupo Santander
📍 Boadilla del Monte