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Santander

Global retail and commercial banking group

Algorithmic Credit Trader - Quantitative Credit Trading

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-timeMadrid, SpainNo salary listed

About the Job

Requirements

  • At least 10 years of experience in algorithmic trading in EUR credit.
  • An 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 within credit markets.
  • Deep understanding of fixed income and credit products, including cash bonds, credit default swaps (CDS), credit indices, exchange-traded funds (ETFs), and portfolio trading solutions.
  • Proven experience developing quantitative models and factor-based investment or trading strategies.
  • Strong programming skills in Python and experience working with large datasets, database architectures, and market data application programming interfaces (APIs).
  • Solid knowledge of statistical modeling, machine learning techniques, and financial market microstructure.
  • Demonstrated experience building pricing engines, risk management systems, and trading analytics platforms.
  • Proven ability to manage large and complex credit risk portfolios, including market-making books with significant balance sheet and risk exposure.
  • Experience trading and hedging credit products using instruments such as CDS indices, ETFs, and cash bonds.
  • Strong understanding of electronic trading venues and market structure across developed and emerging credit markets.
  • English proficiency is required.

Responsibilities

  • Design, build, and maintain proprietary in-house databases and data infrastructure to support systematic credit trading activities.
  • Develop, implement, and continuously enhance algorithmic trading strategies across cash bonds, CDS, indices, ETFs, and other credit products.
  • Establish and manage an independent two-sided algorithmic market-making and trading book across developed and emerging credit markets.
  • Research, develop, and deploy multi-factor quantitative models to identify trading opportunities and generate alpha within systematic credit strategies.
  • Integrate alternative datasets, market microstructure signals, liquidity metrics, and fundamental indicators into trading models.
  • Build pricing engines, risk management frameworks, portfolio analytics, relative value tools, liquidity analysis, client analytics, and execution management capabilities.
  • Monitor and optimize execution quality, transaction costs, and overall trading performance across electronic and voice trading channels.
  • Manage a highly granular profit and loss (P&L) framework, ensuring detailed attribution, risk transparency, and efficient capital deployment.
  • Develop advanced risk analytics and portfolio visualization tools to monitor exposures by region, sector, tenor, liquidity profile, and other relevant risk factors.
  • Partner with technology, quantitative research, data science, and risk management teams to enhance trading infrastructure and strategy scalability.
  • Support market access initiatives, including onboarding electronic trading venues, inter-dealer brokers, and liquidity providers.
  • Contribute to new issue trading, portfolio trading capabilities, ETF market-making activities, and primary market operations where relevant.
  • Ensure adherence to regulatory requirements, risk limits, and governance standards.

Desired Qualifications

  • Experience building end-to-end quantitative trading platforms and systematic trading infrastructure.
  • Knowledge of cloud-based data and computing environments.
  • Familiarity with electronic market-making, automated execution frameworks, and liquidity provision strategies.
  • Experience with Bloomberg Terminal, Bloomberg Data License, TOMS, KDB, Grafana, and other trading and analytics technologies.
  • Experience onboarding trading venues and broker relationships, including MarketAxess, Bloomberg, Tradeweb, and major inter-dealer brokers.
  • Knowledge of ETF primary market processes, creation/redemption workflows, and authorized participant activities.

About the Company

Santander

Global retail and commercial banking group

Santander is a global bank focusing on retail and commercial banking in Europe and the Americas, serving individuals and SMEs with regional franchises and a broad consumer finance arm, plus a Corporate & Investment Banking division for multinational clients. It uses its Gravity cloud platform to migrate core banking and rapidly deploy digital services such as Openbank across markets, combining fintech-style agility with a bank's balance sheet. The bank differentiates itself by marrying a large retail footprint with global CIB capabilities under the One Santander verticals model to boost efficiency and cross-border revenue. Its goals include improving returns on tangible equity and financing the green economy through sustainable finance and renewable energy projects.

Company size
10,001+
Company stage
IPO
Headquarters
Boadilla del Monte, Spain
Founded
1902

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