Quant developer

What the job actually is

A model that only exists in a notebook has not been built yet. The quant developer is the person who takes it from there to a thing that runs inside a budget: reading a live feed, holding a book in memory, pricing under a time limit, and producing a number the desk is willing to trade on.

Most of the job is choosing representations. Which structure makes the operation this system repeats a million times a day cheap? What is the working set, and does it fit in cache? Is this quantity an estimate, where a double is fine, or something that must reconcile, where it has to be an integer? Almost every serious performance problem and almost every silently-wrong number traces back to one of those three questions being answered by habit rather than by measurement.

The other half is reproducibility. A backtest whose answer moves when the thread count changes, or when an unrelated import consumes a random draw, is not a result — it is a rumour. Pinning seeds, fixing reduction orders and testing that a rerun reproduces the number is unglamorous and it is what makes research defensible.

The calls that define it

• Which data structure the hot path is built out of, and what that costs
• Where a computation must be exact and where an estimate is fine
• Whether to spend the memory to buy back the latency
• What gets measured, and what the profile actually says to change

Sits wherever research meets production: execution and market-data infrastructure, pricing and risk libraries, backtesting platforms, and any research group large enough that somebody has to own the code the models run on.

What you'd need to know

The concepts this chair runs on — each one links to a plain-English definition.

Sit in the chair

Reading about a job is the trailer. This simulation makes you do it — free, in the browser, nothing to install and nothing locked.

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