h3Role Overview /h3 pWe have partnered with a leading global asset manager looking to hire a Quantitative Credit Analyst to join its growing Fixed Income team in Zurich. The team manages portfolios worth several billion USD across public and private credit markets, with assets under management continuing to grow significantly. /p pThe successful candidate will work closely with experienced Fixed Income Portfolio Managers across a broad range of credit asset classes. The role will focus on developing quantitative models, analytics and Python-based tools to support investment decisions, portfolio construction, valuations and risk analysis across both public and private credit markets. /p pThe ideal candidate will have a strong quantitative and academic background, excellent Python skills, and experience applying quantitative techniques to fixed income or credit investments. Candidates with experience in public credit, private credit, or a combination of both will be considered, provided they demonstrate strong mathematical foundations and an understanding of fixed income markets. /p h3Key Responsibilities /h3 ul libQuantitative Modelling Analytics: /b Develop, enhance and maintain quantitative models and analytical tools to support investment decisions across a broad range of public and private credit assets. /li libPublic Credit Analytics: /b Work closely with Fixed Income Portfolio Managers covering investment grade corporate bonds, government bonds, high yield credit, leveraged loans and other liquid fixed income instruments, supporting portfolio analytics, pricing, relative value and risk assessment. /li libPrivate Credit Analytics: /b Support investment teams managing private debt portfolios spanning direct lending, infrastructure debt, real estate debt, private placements, asset-backed finance, fund finance and other structured credit investments. /li libFixed Income Modelling: /b Build and enhance analytical frameworks covering bond pricing, yield curves, duration, convexity, credit spreads, cash flow modelling and interest rate sensitivities. /li libPython Development Automation: /b Design and implement Python-based quantitative tools, models and automated analytical processes to improve the efficiency, accuracy and scalability of portfolio analysis. /li libPortfolio Analytics Risk: /b Develop tools to assess portfolio exposures, credit sensitivities, relative value, scenario analysis and risk characteristics across different fixed income asset classes. /li libCross-Team Collaboration: /b Partner closely with Portfolio Managers and investment professionals across public and private credit to deliver actionable quantitative insights and analytical solutions. /li /ul h3Requirements Qualifications /h3 ul libExperience: /b Ideally 2 to 7 years of relevant experience in quantitative research, fixed income analytics, credit portfolio analytics, quantitative development, or a related role within an asset manager, investment bank or other financial institution. /li libAcademic Background: /b Strong academic credentials, ideally with a degree in Mathematics, Physics, Engineering, Computer Science, Financial Engineering, Quantitative Finance or another highly quantitative discipline. /li libCredit Markets Knowledge: /b Experience working with public and/or private credit investments, with a good understanding of fixed income instruments, their underlying characteristics, and the key drivers of risk and return. /li libFixed Income Mathematics: /b Strong understanding of bond mathematics, including pricing, yield curves, duration, convexity, spread duration, DV01, interest rate sensitivities and credit spread analysis. /li libPython Programming: /b Excellent Python programming skills are essential, with demonstrated experience developing quantitative models, analytical tools or automated processes. Experience with libraries such as NumPy and pandas is highly advantageous. /li libQuantitative Expertise: /b Strong mathematical and analytical capabilities, with knowledge of statistical modelling, numerical methods, probability, optimisation, Monte Carlo simulations or other quantitative techniques. /li libData Analysis: /b Ability to work with large and complex financial datasets, develop sound analytical frameworks, and translate quantitative outputs into practical investment insights. /li libProblem-Solving: /b Strong intellectual curiosity and the ability to approach complex, sometimes loosely defined analytical problems independently, developing practical and efficient solutions. /li libCommunication Collaboration: /b Ability to work effectively with Portfolio Managers and investment professionals, clearly communicating quantitative concepts and analytical findings. /li libCultural Fit: /b Highly motivated, intellectually curious, detail-oriented, and comfortable working in a dynamic, collaborative and high-performing investment environment. /li /ul pThe successful candidate will join a market-leading Fixed Income team at a global asset manager, gaining exposure to a diverse range of public and private credit investments while helping to develop and expand the team's quantitative analytics and modelling capabilities. /p
Quantitative Credit Analyst Arbeitgeber: Laz Partners
Als Arbeitgeber in Zürich bietet unser Unternehmen eine dynamische und unternehmerische Arbeitsumgebung, die auf Wachstum und Innovation ausgerichtet ist. Wir fördern eine Kultur der Zusammenarbeit und des Wissensaustauschs, in der Mitarbeiter die Möglichkeit haben, ihre Fähigkeiten weiterzuentwickeln und aktiv an der Gestaltung unserer Cash- und Liquiditätsportfolios mitzuwirken. Mit einem starken Fokus auf quantitative Analysen und modernste Technologien bieten wir nicht nur ein wettbewerbsfähiges Gehalt, sondern auch die Chance, Teil eines hochprofitablen Teams zu werden, das in einem spannenden europäischen Markt tätig ist.
