Bloomberg’s evaluated pricing service, BVAL, is Bloomberg’s flagship product in the fixed income valuation market and a primary pricing source for Bloomberg Fixed Income Indices. BVAL distinguishes itself from competitors by offering superior transparency and defensibility of pricing at current and historical snapshots, along with 24/7 global customer support. BVAL prices are driven by a wealth of high-quality, real-time market data using sophisticated asset-class specific relative value models. BVAL prices are made available on the Terminal and via enterprise feed. 

We in the BVAL Quant group design and develop a suite of methodologies to price approximately 2.7 million securities. Our pricing provides traders, portfolio/risk managers, analysts and auditors with an accurate reference price in a market that typically does not have a central exchange for trading.  Our pricing engines ingest billions of incoming market quotes per day and run them through pricing models. The BVAL Quant group is distributed between the Bloomberg offices in New York and London. In addition to fixed income pricing, the BVAL Quant group also supports other initiatives such as ESG, paving the way for cross-pollination of ideas between different initiatives. 

We’ll trust you to

• Design proprietary methodologies using Machine Learning and enhance them into real-world design suitable for deployment on Bloomberg platforms
• Work closely with other BVAL engineering teams to implement and deploy solutions compatible with the capabilities and limitations of the engineering infrastructure
• Build model validation, back-testing, and testing procedures for pricing solutions across multiple asset-classes
• Write and maintain production quality code and systems
• Communicate clearly through meetings and presentations within the team as well as with other stakeholder groups

You’ll need to have

• Proven experience in quantitative analysis techniques including statistical analysis and machine learning over diverse data sources and formats
• Intuitive understanding of model features and their connection with real-world client needs, and ability to convey this understanding to non-technical audiences
• Ability to quickly learn from emerging trends in financial markets
• Experience in at least one modern programming language such as Python
• Strong verbal and written communication skills
• BA, BSc, MSc, PhD in applied quantitative field such as Statistics, Engineering or Quantitative Finance or relevant experience in the technology field

We’d love to see

• Experience with production quality software development life cycle and practices
• Background and/or exposure to financial markets, especially fixed income domain
• Experience in C++ programming language and/or willingness to learn C++

Bloomberg is an equal opportunities employer, and we 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.