Algorithmic Credit Trader (Quantitative Credit Trading)

About the role

Santander Corporate & Investment Banking is looking for an Algorithmic Credit Trader based in Madrid. The role covers systematic credit trading, including market making and trading across cash bonds, CDS, indices, ETFs and other credit products, and requires strong quantitative modelling and programming skills.

Key responsibilities

• Design, build and maintain proprietary in-house databases and data infrastructure for systematic credit trading.
• Develop, implement and enhance algorithmic trading strategies across cash bonds, CDS, indices, ETFs and other credit products.
• Manage an independent two-sided algorithmic market-making and trading book across DM and EM credit markets.
• Research, develop and deploy multi-factor quantitative models, integrating alternative data, market microstructure signals, liquidity metrics and fundamentals.
• Build pricing engines, risk management frameworks, portfolio analytics, relative value tools, liquidity and client analytics, and execution management capabilities.
• Monitor execution quality, transaction costs and trading performance across electronic and voice channels, and manage a detailed P&L framework.
• Develop risk analytics and portfolio visualization tools, and partner with technology, research, data science and risk teams.
• Support market access, new issue and ETF market-making activities, and ensure compliance with regulations and risk limits.

Required profile

• 10 years of experience in algo trading in EUR credit.
• Advanced degree in Quantitative Finance, Mathematics, Statistics, Physics, Engineering, Computer Science or a related quantitative discipline.
• Strong experience in systematic, algorithmic or electronic trading, preferably in credit markets.
• Deep understanding of fixed income and credit products, and proven experience building quantitative models and factor-based strategies.
• Proven ability to manage large credit risk portfolios and market-making books.
• Preferred: experience building end-to-end quantitative trading platforms, cloud data environments, and onboarding trading venues and brokers.

Required skills

• Python and experience with large datasets, database architectures and market data APIs.
• Statistical modelling, machine learning and market microstructure.
• Building pricing engines, risk systems and trading analytics platforms.
• Preferred: Bloomberg Terminal, KDB, Grafana, MarketAxess, Tradeweb, and ETF primary market knowledge.

What we offer

• Hybrid working model with flexible hours.
• Competitive salary with performance-based bonuses.
• Preferential banking terms, life insurance and wellness programmes.
• Childcare support, employee family advisory services and employee discounts.