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Bloomberg is building the world’s most trusted information network for financial professionals. Our 6,500+ engineers are dedicated to advancing and building new systems for the Bloomberg Terminal to solve complex, real-world problems. We trust our teams to choose the right technologies for the job, and, at Bloomberg, the answer is often Python. We employ an active community of 2,000+ Python developers who have their hands in everything from financial analytics and data science to contributing to open source technologies like Project Jupyter. Bloomberg is proud to be a visionary sponsor of the Python Software Foundation and host of many Python community events around the world.
Two Sigma is a financial sciences company. We combine rigorous inquiry, data analysis, and invention to solve the toughest challenges across financial services. We use Open Source Software, and we’re passionate about giving back to the programming community. We want to make sure that the OSS projects that we and so many others rely on will still be functional far into the future. Supporting OSS can take many forms: making substantial contributions to projects we use regularly, open sourcing tools we’ve developed in house, and financially sponsoring non-profits that contribute to a healthy open source ecosystem.
Bank of Americacareers.bankofamerica.com/mycareer/en-us/job-detail/21045554/python-software-engineer-iii-new-york-new-york-united-states
Quartz is a massive Python development initiative that is revolutionizing the Global Markets business at Bank of America. Quartz is the primary platform for pricing trades, managing positions, and computing risk exposure. Our technology stack includes globally distributed object-oriented databases, Linux compute farms, and advanced quant libraries. Thousands of developers are using the highly-agile platform to deliver applications to thousands of end users.
We are an organization with a product-oriented mindset that prioritizes quality, engineering and teamwork. We are looking for exceptional software engineers from diverse backgrounds who can lead, or significantly contribute to, enterprise technology delivery. A background in Big Data, Data Science, DevOps or large-scale architecture is ideal. FinTech experience is nice to have.