Bloomberg
Who we are
The Bloomberg CTO Office is the future‑looking technical arm of Bloomberg L.P. We envision, design and prototype the next generation infrastructure, hardware and applications that interface in all aspects of the company including financial products, broadcast and media, data centers, internal IT and our global network. We are passionate about what we do.
What we do BQuant is Bloomberg’s cloud‑hosted quantitative investment research platform, built on JupyterLab and designed specifically for financial markets. As the centralized BQuant Research team, we drive product innovation through cutting‑edge research in generative AI, agentic workflows, machine learning, NLP and quantitative finance. We work across asset classes and market domains to prototype next‑generation solutions for buy‑side and sell‑side institutions (hedge funds, asset managers and investment banks). Our mission is to help clients accelerate their research, portfolio decisions and trade execution by leveraging the unique combination of Bloomberg’s financial datasets, advanced ML/AI and domain expertise. We work at the forefront of AI in capital markets – tackling challenges in equity, fixed income, macro and multi‑asset workflows. Our team operates in a highly collaborative environment, engaging with product managers, engineers, UX designers and sales to deliver transformative client solutions.
What’s in it for you Bloomberg offers the richest and most comprehensive financial datasets across asset classes in the world, paired with extensive product offerings from data to analytics to trading and investment management.
You will have the opportunity to:
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.
The problems you’ll work on are
complex, cutting‑edge and highly impactful
– spanning everything from signal research to portfolio construction to macroeconomic modeling and cross‑asset investment strategies.
You’ll need to have
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.
Excellent collaboration skills with quants, researchers and engineers.
Strong communication skills to engage internal stakeholders and external clients.
We’d like to see
Research experience in multi‑asset and cross‑asset strategies, with preference for FI and Macro.
Deep curiosity and passion for
generative AI, NLP and agentic workflow automation
in finance.
A track record of overcoming complex technical and financial challenges through collaboration and innovation.
#J-18808-Ljbffr
What we do BQuant is Bloomberg’s cloud‑hosted quantitative investment research platform, built on JupyterLab and designed specifically for financial markets. As the centralized BQuant Research team, we drive product innovation through cutting‑edge research in generative AI, agentic workflows, machine learning, NLP and quantitative finance. We work across asset classes and market domains to prototype next‑generation solutions for buy‑side and sell‑side institutions (hedge funds, asset managers and investment banks). Our mission is to help clients accelerate their research, portfolio decisions and trade execution by leveraging the unique combination of Bloomberg’s financial datasets, advanced ML/AI and domain expertise. We work at the forefront of AI in capital markets – tackling challenges in equity, fixed income, macro and multi‑asset workflows. Our team operates in a highly collaborative environment, engaging with product managers, engineers, UX designers and sales to deliver transformative client solutions.
What’s in it for you Bloomberg offers the richest and most comprehensive financial datasets across asset classes in the world, paired with extensive product offerings from data to analytics to trading and investment management.
You will have the opportunity to:
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.
The problems you’ll work on are
complex, cutting‑edge and highly impactful
– spanning everything from signal research to portfolio construction to macroeconomic modeling and cross‑asset investment strategies.
You’ll need to have
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.
Excellent collaboration skills with quants, researchers and engineers.
Strong communication skills to engage internal stakeholders and external clients.
We’d like to see
Research experience in multi‑asset and cross‑asset strategies, with preference for FI and Macro.
Deep curiosity and passion for
generative AI, NLP and agentic workflow automation
in finance.
A track record of overcoming complex technical and financial challenges through collaboration and innovation.
#J-18808-Ljbffr