DRW is a diversified trading firm with over three 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 trade 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 is not just what we do that matters—it is 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
- PhD or MSc in a quantitative discipline such as financial mathematics, operations research, statistics, physics, or economics.
- 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.