Bloomberg is the global leader in business and financial data, news and insight. Using the power of technology, we connect the world's decision makers to accurate information on the financial markets - and help them make faster, smarter decisions.
Finance is changing, and fast; new financial professionals are even learning Python themselves. Here in our San Francisco office we've identified an opportunity to reach this tech savvy client base by building a product that opens up our data, core products and visualizations to data scientists, ML researchers, and quantitative modelers.
Gone are the days of downloading raw CSV files. Bloomberg's BQuant platform allows users to bring their algorithms to our data, not the other way around. Our service provides a unified environment where users can develop their code and test, share, and deploy it easily. Our impact? Providing the entire industry with tools that are currently only available to large banks and hedge funds, through customer deployed installations in enterprise environments.
Within the BQuant platform, the Quant Research Data Platform team develops the APIs and scalable backend infrastructure to capture the artifacts that are produced during quantitative research workflows such as factor scoring and backtesting. Such workflows are used to identify market signals that should be used as the basis for portfolio construction and to determine how these strategies impact portfolio returns. These workflows are computationally expensive but also produce a large number of artifacts (factors, factor models and strategy definitions, large volumes of intermediate and derived time series data). This introduces the need for scalable backend infrastructure that provides primitives for tagging, versioning, sharing and other experiment management features to be layered on top.
Come help us build a novel infrastructure that pushes the financial industry into the next generation.
We'll trust you to:
Develop intuitive APIs for customers to utilize Bloomberg's data and services in novel ways
Have a good sense for working with heterogeneous datasets (data modelling, experience with document and timeseries databases)
Adopt a test-driven mentality to developing code
You need to have:
5+ years using Python, C++ or another object oriented language in a production system
BA, BS, MS, PhD in Computer Science, Engineering or related technology field
A strong familiarity with Continuous Integration and Continuous Deployment methodologies
Experience building and supporting production systems
Bloomberg is an equal opportunities employer, and we 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.