How a hedge fund cut simulation time from days to hours with a modern Python stack

Double River is a quantitative hedge fund that modernized their Python stack to scale international equity trading simulations. Nelson Griffiths (Head of Engineering) explains how they eliminated computational bottlenecks limiting their trading strategy development. Their setup: - Polars for data manipulation - Prefect for workflow orchestration - Snowflake for scalable data storage - Coiled for scalable GCP compute access Result: More strategy testing capacity and engineering focus on value creation over infrastructure. Applicable for data engineers, quant analysts, and teams building compute-intensive Python applications. Read the full case study: https://coiled.io/customers/double-river