Bloomberg L.P.
Senior Quantitative Developer - BQuant Research Platform
Bloomberg L.P., San Francisco, California, United States, 94199
Senior Quantitative Developer - BQuant Research Platform in San Francisco, California
BQuant is Bloomberg’s cutting edge financial research and data science platform. With the tremendous growth of market data and the increasing sophistication of machine learning and quantitative methods, finance is quickly becoming a business where only the best capitalized firms can compete. BQuant’s mission is to change that, by empowering researchers and investment decision makers around the world with the sophisticated tools that are currently only available to the largest investment firms. Our team is developing a suite of new, cloud-native products for systematic and quantamental investment workflows. We are designing these products to scale to a broad and diverse client base of hedge funds, asset managers, and investment banks who need to run decades-long backtests of complex strategies that depend on traditional and cross-asset signals, alternative data, and machine learning techniques. We seamlessly integrate with Bloomberg’s massive troves of high quality market data, and make use of a modern technology stack which includes both in-house solutions and open-source packages such as Pandas, PySpark, Scikit-learn, and PyTorch. We are looking for a senior quantitative developer with experience in building systems for quantitative investing, including signal generation, portfolio construction, backtesting, and advanced analytics. This is a fantastic opportunity for an entrepreneurial individual to join a growing team, apply open-source technology at scale, and help shape a strategic product with industry-wide impact. We’ll trust you to: Develop a modular framework for implementing and evaluating systematic trading strategies, including signal generation, portfolio construction, and backtesting. Create APIs that are intuitive to quant practitioners. Work hand-in-hand with Bloomberg quantitative researchers to prototype and iterate on new product ideas. Think about how our solutions can be used for both research and production. Collaborate across teams. You’ll need to have: 4+ years of experience as a quantitative developer writing production-quality Python at financial technology firms. Broad experience developing software for quantitative investment workflows in equities, fixed income, or multi-asset strategies. Experience working with large financial datasets, in time series or other structures. The ability to work cross-functionally with software engineers, quant researchers, and product managers. A Bachelor, Masters, or PhD in a quantitative field, such as computer science, computational finance, financial engineering, or mathematics. We’d love to see: Financial domain knowledge in multiple asset classes. Production-level experience with Python’s numerical and machine learning packages.
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BQuant is Bloomberg’s cutting edge financial research and data science platform. With the tremendous growth of market data and the increasing sophistication of machine learning and quantitative methods, finance is quickly becoming a business where only the best capitalized firms can compete. BQuant’s mission is to change that, by empowering researchers and investment decision makers around the world with the sophisticated tools that are currently only available to the largest investment firms. Our team is developing a suite of new, cloud-native products for systematic and quantamental investment workflows. We are designing these products to scale to a broad and diverse client base of hedge funds, asset managers, and investment banks who need to run decades-long backtests of complex strategies that depend on traditional and cross-asset signals, alternative data, and machine learning techniques. We seamlessly integrate with Bloomberg’s massive troves of high quality market data, and make use of a modern technology stack which includes both in-house solutions and open-source packages such as Pandas, PySpark, Scikit-learn, and PyTorch. We are looking for a senior quantitative developer with experience in building systems for quantitative investing, including signal generation, portfolio construction, backtesting, and advanced analytics. This is a fantastic opportunity for an entrepreneurial individual to join a growing team, apply open-source technology at scale, and help shape a strategic product with industry-wide impact. We’ll trust you to: Develop a modular framework for implementing and evaluating systematic trading strategies, including signal generation, portfolio construction, and backtesting. Create APIs that are intuitive to quant practitioners. Work hand-in-hand with Bloomberg quantitative researchers to prototype and iterate on new product ideas. Think about how our solutions can be used for both research and production. Collaborate across teams. You’ll need to have: 4+ years of experience as a quantitative developer writing production-quality Python at financial technology firms. Broad experience developing software for quantitative investment workflows in equities, fixed income, or multi-asset strategies. Experience working with large financial datasets, in time series or other structures. The ability to work cross-functionally with software engineers, quant researchers, and product managers. A Bachelor, Masters, or PhD in a quantitative field, such as computer science, computational finance, financial engineering, or mathematics. We’d love to see: Financial domain knowledge in multiple asset classes. Production-level experience with Python’s numerical and machine learning packages.
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