Bloomberg Portfolio Analytics (PORT) empowers the most prominent players in the financial world to manage their portfolios, assess exposures, and make informed decisions that move markets. Our flagship product on the Bloomberg Professional Service is a critical tool used daily by money managers, mutual funds, hedge funds, and pension funds around the world. PORT provides industry-leading quantitative financial tools and overnight batch report generation.
The PORT Risk team crafts calculators for risk analytics including VaR & Tracking Error using various methodologies such as Monte Carlo, simulations, and parametric. Our portfolio optimization products automatically rebalance a user's portfolio given a specific user-defined strategy of goals, constraints, and trading universes that are mapped to a mixed-integer quadratic problem. We utilize a variety of modern technologies including C++, quantitative libraries, CPLEX, Redis, Apache Spark, Cassandra, and machine learning. Our latest high-profile initiative is opening up APIs to allow sophisticated users to access the risk analytics and optimization engines programmatically.
The PORT Performance Attribution Integration team focuses on creating and using flexible integration points to support our Performance and Attribution models. These models are highly customizable and continually expanding to provide the best possible product for our many different clients. We work closely with product and research to plan and complete our work to ensure we align with our clients needs. We primarily develop C++ and python service and libraries running on linux, using S3 based storage. Recently we have started building our next generation Multi-Asset Class Hybrid Performance and Attribution model to provide the latest in Performance Attribution analytics.
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.
Job ID: 75862
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