Quant Researcher - Compute Markets in London

Quant Researcher - Compute Markets in London

London Full-Time 63000 - 77000 £ / year (est.) On-site
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At a Glance

  • Tasks: Build innovative pricing frameworks for emerging compute markets and collaborate with trading teams.
  • Company: DRW, a leading trading firm with a culture of integrity and innovation.
  • Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
  • Other info: Dynamic workplace with high expectations and a focus on collaboration.
  • Why this job: Join a pioneering team shaping the future of trading in compute capacity.
  • Qualifications: Strong Python skills and ability to build pricing models from scratch.

The predicted salary is between 63000 - 77000 £ per year.

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.

We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.

S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets.

We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.

DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

Quantitative Researcher — Compute Markets

We are building the pricing infrastructure for a market that does not yet have any.

Compute capacity is becoming a tradeable asset: spot indices exist, listed futures are in development, and bilateral forward and structured transactions are already being negotiated.

Almost nobody transacting in this market can price the underlying risk.

We intend to.

  • What you would do
  • Build and own the pricing framework for forward, structured and credit-linked transactions on compute capacity, including forward curve construction on an asset with no observable forward market.
  • Produce reservation bids and offers on bilateral requests, and defend them internally.
  • Own the valuation model for the book, to a standard that survives institutional operational due diligence.
  • Work directly with trading, risk and the firm's leadership on transaction structure, not only on the numbers.
  • What we are looking for
  • Demonstrated ability to build a price from structural first principles where market data is sparse or absent.

Prior work on commodities, energy, freight, weather, insurance-linked or other physically-grounded markets is directly relevant, though not required.

  • Fluency in Python, and comfort with Monte Carlo methods and uncertainty quantification.
  • The temperament to state an assumption, own it, and change it when the evidence moves.
  • Prior exposure to compute or semiconductor markets is not expected and will not be weighted.

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Quant Researcher - Compute Markets in London employer: DRW Holdings, LLC.

At DRW Holdings, LLC., we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to excel in their roles. As a Quant Research Engineer, you will have access to cutting-edge technology and resources, alongside opportunities for professional growth and collaboration with top-tier talent in the finance sector. Located in a vibrant trading hub, we offer a stimulating environment where your contributions directly impact our trading strategies and success.

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Contact Details:

DRW Holdings, LLC. Recruitment Team

We think you need these skills to ace Quant Researcher - Compute Markets in London

Pricing Framework Development
Forward Curve Construction
Valuation Model Ownership
Quantitative Analysis
Python Programming
Monte Carlo Methods
Uncertainty Quantification