Bloomberg is looking to solve complex, cutting-edge problems in the financial industry by leveraging generative AI, agentic workflows, machine learning, NLP, and quantitative finance to accelerate research, portfolio decisions, and trade execution for buy-side and sell-side institutions.
Requirements
- 10+ years in quantitative research, machine learning, or financial AI development, including 5+ years in capital markets (fixed income, macro, or equity)
- Prior experience designing and deploying GenAI solutions or agentic workflows in a financial market context
- Advanced degree (Masters/PhD) in a quantitative field (e.g., Computer Science, Financial Engineering, Statistics, Applied Math, Physics)
- Strong foundation in statistics, ML, and AI, with proven real-world applications in finance
- Strong programming skills in Python and familiarity with ML/AI libraries
Responsibilities
- Build generative AI and agentic workflow solutions that redefine how the financial industry conducts research, trading, and risk management.
- Apply advanced ML/AI techniques in an extremely rich problem space with high impact potential across hedge funds, asset managers, and investment banks.
- Own the full lifecycle of innovation: ideation, prototyping, validation with clients (including top-tier buy-side and sell-side firms), and delivery to production in collaboration with engineering teams.
- Shape how Bloomberg clients use ML/AI to evolve from research to production in scalable, efficient, and reliable ways.
- Work on complex, cutting-edge, and highly impactful problems spanning everything from signal research, to portfolio construction, and to macroeconomic modeling and cross-asset investment strategies.
Other
- Excellent collaboration skills with quants, researchers, and engineers
- Strong communication skills to engage internal stakeholders and external clients
- Advanced degree (Masters/PhD) in a quantitative field
- 5+ years in capital markets (fixed income, macro, or equity)
- Research experience in multi-asset and cross-asset strategies, with preference for FI and Macro
