We're Bloomberg. We sit at the heart of the financial markets, from the largest sell-side institutions right through to the two-person hedge fund - we're an integral part of the financial markets workflow in every corner of the world. We provide our users with up-to-the-millisecond market moves and analytics as well as connecting them with their counterparts and the wider community of Bloomberg Terminal subscribers.

Our Trading Automation & Analytics team consists of physicists and mathematicians who built their careers with major asset managers, hedge funds and broker dealers across Equities, Fixed Income and FX trading. We see an opportunity in financial industry to create advanced trading tools and to make the markets more efficient. The innovative decision support tools and state-of-the-art quantitative models we build help traders, portfolio managers, and CIOs to make important decisions across the buy-side and sell-side.

Our Quants are resourceful, adaptable and collaborative. They combine their technical skills and product knowledge to craft unsurpassed solutions for our customers. If you are a creative, open-minded, and results-oriented quant – keep reading.

What's the role?

As a member of the Trading Research Quant team you will work with various asset classes, contributing to decision making and trading strategies. Trade Cost Analysis (TCA), Broker-Algo selecting tools, crowd-sourcing, market impact and trading optimizations are all part of this process.

We will trust you to:

• Create innovative frameworks and state-of-the-art quantitative models for a variety of our clients and job functions including traders, portfolio managers and CIOs.
• Participate in the full life-cycle workflow from hypothesis formulation, research and prototyping through to production release to clients.

You will need to have:

• MS in science/math/operations research/quant finance or equivalent experience
• Proven knowledge of calculus and stochastic processes
• 4+ years of financial industry experience in FX, Bonds, Equities or Futures
• Experience building advanced statistical methods
• Numerical programming experience in Python

We'd love to see:

• Expertise in market microstructure, trading algorithms and TCA
• Multi-asset experience
• Knowledge of Machine Learning Algorithms
• Solid programming experience, preferably with Python