Senior Quant Researcher, Enterprise Product

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 325,000 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, alpha and risk modeling, market impact and optimizations are all part of this process.
We will trust you to:

• Participate in the full life-cycle workflow from hypothesis formulation, research and prototyping through to production release to clients.
• 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.

You will need to have:

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

We'd love to see:

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

• Please note we use years of experience as a guide, but we will certainly consider applications from all candidates who are able to demonstrate the skills necessary for the role.

Apply if you think we're a good match. We'll get in touch to let you know the next steps, but in the meantime feel free to browse this: http://www.bloomberg.com/professional
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.
Salary Range: 155,000 - 285,000 USD Annually + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation [Exempt roles only], paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.