Quantitative Engineer

Description:

Bloomberg’s Engineering AI department, comprising over 350 AI practitioners, is expanding its Fixed Income team to develop state-of-the-art ML and statistical models for pricing millions of securities across diverse asset classes. The Senior Quantitative Engineer will design, build, and evaluate advanced machine learning models, integrating modern techniques with Bloomberg’s proprietary technology and large-scale datasets. The role requires contributing novel modeling ideas, writing clean, modular production-quality code for cloud-native environments, and collaborating with cross-functional teams to develop robust systems.

Key Responsibilities:

• Design, build, and evaluate ML and statistical models for financial asset pricing, with a focus on Fixed Income

• Collaborate with engineering and cross-functional teams to develop, test, monitor, and maintain production systems

• Design architectures, systems, and tools to enhance Bloomberg’s next-generation pricing capabilities

• Integrate cutting-edge academic and industry research into models and methodologies

• Represent Bloomberg at scientific and industry conferences; publish research findings through documentation, whitepapers, or leading academic journals

Candidate Requirements:

• Ph.D. or M.Sc. with equivalent research experience in Machine Learning, Computer Science, Mathematics, Statistics, or related field

• Expertise in Fixed Income modeling, interest rate theory, credit risk, or advanced statistical/ML techniques

• Strong software engineering skills and understanding of computer science fundamentals, including data structures and algorithms

• Ability to solve challenging, ill-defined problems creatively and rigorously

• Excellent communication skills to collaborate with both technical and non-technical stakeholders

• Publications in top conferences or journals are a strong plus