The Core Financial Analytics team provides the foundational pricing, analytics, and data infrastructure that powers Bloomberg’s markets business. The group delivers cross-asset solutions for curves, volatility surfaces, consensus pricing, screening tools, and listed derivatives, ensuring that clients and internal systems have access to accurate, transparent, and real-time market data.

The CFA department is made up of four specialized teams:

The Market Data Analytics team delivers high-performance, cross-asset market data systems that power critical pricing, risk, and analytics for Bloomberg’s Terminal and Enterprise clients. The team builds scalable, adaptable platforms that transform raw market inputs into precise, normalized datasets—fueling accurate valuations, informed decision-making, and regulatory compliance across global financial markets.

The Core Data Analysis team delivers descriptive reference data, relative value analytics, factor analysis and back-testing capabilities for our clients’ data in Fixed Income and Equity worlds. We provide intuitive and easily discoverable universe creation of securities, help clients execute complex relative valuations across those universes, and provide insight to how securities compare with each other and their own history over time. We do all of this using our large scale data stores and distributed systems.

The FX & Commodity Pricing team develops cutting-edge pricing systems for global currency and commodity markets, producing real-time FX rates and fair values for commodities such as oil, gas, metals, and agricultural products. Leveraging modern C++20, advanced algorithms, and a robust data lake ecosystem, the team delivers transparent, accurate, and high-quality pricing that powers trading, valuation, risk management, and regulatory workflows worldwide.

The Futures & Options (F&O) team empowers key market participants by providing tools and insights for idea generation, real-time market surveillance, historical analysis, volatility monitoring and more. Our product coverage spans options, futures, and warrants for products including equities, commodities, interest rates, bonds, and currency exchange rates across all major global markets. Our team plays a critical role in enabling the firm’s derivatives ecosystem by delivering the foundational framework and services that support all consumers of listed derivatives data.

What’s in it for you?
As a member of the Core Financial Analytics team, you'll contribute to a high-performance financial software system that handles billions of calculations per day. You'll gain hands-on experience in data analytics, distributed algorithms, and performance optimized code, all while gaining an advanced knowledge of financial instruments and markets. We seek passionate engineers who thrive in a diverse, collaborative environment and excel at crafting reusable, efficient solutions to complex problems. Proficiency in object-oriented programming languages like C++, Python, or TypeScript is greatly desired, with a willingness to learn new technologies. You will also have the opportunity to leverage open-source tools like Apache Kafka, Spark, Solr, Clickhouse, Cassandra and Redis (plus many more!) to design, develop, and implement full-stack solutions, adhering to industry best practices for software development, testing, automation, and CI/CD.

You'll need to have:

• 4+ years working with an object-oriented programming language (C/C++, Python, Java, etc.)

• A degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience

• Proficiency in system design, architecture, and development of high-quality, modular, stable, and scalable software

• Passion for leading discussions, sharing innovative ideas, and promoting best practices within the team

• Proficient in adapting project execution to meet evolving demands
  
  

We'd love to see:

• Experience with other programming languages such as Javascript, Scala, and OCaml

• An interest in financial markets or a background in data analytics or financial engineering

• Comfort with high volume, high availability distributed systems