Senior Software Engineer - PORT Modeling, Risk & Attribution (FA - Financial Analytics)
New York, NY
Posted Aug 3, 2022 - Requisition No. 100700
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.
Some Current and Upcoming Projects:
- Building a new integration layer for new and existing Portfolio Analytic applications.
- Building out client facing transparency tools to break down return and attribution trends and values
- Integrating PORT’s newly redesigned enterprise version of the UI with our backend
- Develop the next generation of industry leading risk models to increase the predictive power and improve asset coverage significantly
- Build out algorithms for optimizing portfolios in close collaboration with research team
- Develop APIs and tools for clients to access services in a scalable fashion
What you can expect if you join our team:
- Fast paced work with direct client impact
- Work closely product, QA, research, and other engineering teams in the US, London, and Lugano to create the best possible product
- Grow your financial domain knowledge as you work on a product that covers a wide array of asset classes, portfolio types, and investment approaches
You’ll need to have:
- 3+ Years of programming experience in C++, Java, or Python
- Strong communication and collaboration skills
- Strong problem solving skills and ability to adapt to challenges
- Experience covering the full software development life cycle
- a bachelor’s degree in computer science or a related field, and/or
- an equivalent combination of education, and/or
- specialized training, and/or
- related professional experience
This position requires at least one of the following:
We would love to see:
- Enthusiasm to learn and to improve the product
- Interest in understanding the financial concepts related to performance and attribution
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
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