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 new cloud-hosted quantitative investment research platform built on JupyterLab that is designed specifically for financial markets.
As the centralized BQuant Research team, we are committed to empowering BQuant product innovation through cutting-edge research and prototype development across all product areas, by leveraging advanced techniques in quantitative finance, ML, NLP, and AI in general. Our team of experts is involved in every step of the process, from ideation to prototype, to client engagement for validation, and we work collaboratively with product managers, engineering, UX designers, and sales teams to bring product ideas to life.
What’s In It For You
At Bloomberg, we have the richest and most comprehensive financial datasets across asset classes in the world. This offers a great opportunity for innovation by marrying technology in Machine Learning (ML) with our data and financial libraries. We have extensive product offerings from data to analytics to trading and investment management products that serve a broad client base in finance.
We have a unique opportunity to explore cutting-edge ML techniques in combination with financial domain expertise in an extremely rich problem space, and to build applications that demonstrate how those technologies can be delivered to our clients via BQuant and the Terminal. You will use a wide selection of datasets, tools, and libraries to develop solutions in trading and investment processes. You’ll shape the vision of how our clients can accelerate their research to production evolution in an efficient and scalable way. This involves data access, financial modeling with ML or quantitative methods, sound testing and evaluation, such that it is reproducible and can be adapted to clients’ use cases in an efficient way.
As applying ML in finance is still at an early stage, the potential of business impact and influence on the industry can be tremendous when it is applied appropriately. You will own the whole process from ideation to building prototypes, and to working with engineering teams to deliver to our clients. You will collaborate with teams of top-notch quants, ML researchers, and engineers.
You’ll Need To Have
- 10+ years in quantitative/machine learning research and development, including 5+ years in the equity space
- Broad platform experience from strategy research to portfolio implementation, risk management, and performance analysis, across asset classes
- Masters or PhD in quantitative fields
- Solid foundation in Statistics and ML, and successes in applying them in the past
- Programming skills in Python
- Ability to collaborate with quants and ML teams and drive initiatives
- Ability to communicate with internal stakeholders and external clients effectively
We’d Like To See
- Research experience in multi-asset strategies, beyond equity
- Passion about applying ML/NLP techniques in finance with domain expertise
- Determination to overcome challenges through collaborative efforts
