Bloomberg's Engineering AI department is looking to solve challenges in fixed income modeling by designing and implementing advanced models that leverage modern ML and statistical techniques on top of novel technology stacks and vast data sources to price millions of securities accurately.
Requirements
- 3+ years of relevant work experience with Machine Learning or Statistical Modeling techniques in the financial industry ideally around asset valuation.
- Ph.D. or M.Sc. with equivalent research experience in Machine Learning, Computer Science, Mathematics, Statistics or a related field.
- Thriving in solving challenging, often ill-defined problems where off-the-shelf solutions fall short, and bring a creative, rigorous approach to developing novel methods and technologies.
- Proven track record designing, building, evaluating and maintaining statistical or Machine Learning solutions on Production.
- Proficiency in software engineering with an understanding of Computer Science fundamentals such as data structures and algorithms.
- A track record of authoring publications in top conferences and journals is a strong plus
Responsibilities
- Develop, build and evaluate statistical and Machine Learning models that directly influence how global markets price fixed income assets.
- Collaborate with cross-functional teams to develop, test, monitor and maintain robust production systems.
- Design new architectures, systems and approaches to power the pricing capabilities of Bloomberg.
- Integrate cutting-edge academic and industry research into models and methodologies, staying ahead of emerging developments to drive continuous innovations.
- Represent Bloomberg at scientific and industry conferences, and publish research findings through documentation, whitepapers, or in leading academic journals and conferences.
Other
- Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders.
