Financial Machine Learning and Quant Researcher - CTO Office
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:
The CTO Data Science department is a dynamic, collaborative and intellectually stimulating environment - the work is always exciting and the challenges we encounter are never boring. From this department we guide the company's overall strategic direction for machine learning, natural language processing, and search throughout the entire business. We are transforming our business through these technologies as well as the insights we provide our customers across the global financial sector.
At Bloomberg, our systems ingest hundreds of billions of market data ticks and millions of curated news stories for financial players to process and make investment decisions. The CTO Data Science department's machine learning efforts enhance our clients' ability to find the right pieces of information that are vital for continued success in their jobs. 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. One of our offerings is Bloomberg Quant (BQNT), a development platform for quants to rapidly analyze data and research trading strategies, with the Bloomberg Query Language (BQL) to access data and services.
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 BQNT 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 implementation, and to delivery via BQNT and the Terminal. You will collaborate with teams of top-notch quants and ML researchers. You'll need to have:
- 5+ years in quantitative research in equities, fixed income, commodities, and currencies
- Broad experience from trading strategy development to risk management and performance analysis
- 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 We'd like to see:
- Passion about applying ML techniques in finance with domain expertise
- System design and software architecture experience
- Multi-asset class experience, including futures and options
- Determination to overcome challenges through collaborative efforts
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.