Python Developer

Perhaps one of the most interesting reasons to leverage your Python expertise in a medium frequency trading team is largely because latency in this instance is measured in a very different way. What we're talking about here isn't the speed at which your trading strategy can be executed on an exchange via colocation, it will be how you are personally colocated with the researchers building the model where their search for profit resides; how quickly are you able to implement this idea and test its profitability? Whilst you can expect to be in an extremely intellectually challenging environment, this won't look like many other types of industries. Expect to be testing new ideas daily and have extremely high levels of collaboration across different areas of this team. Here's what you can expect to work on: Direct access to signal intent where you'll catch alpha decay and regime shifts before they hit production Prevent backtest-to-production parity bugs (data snapshots, fills, resampling, timezone drift) Catch look-ahead bias and point-in-time data issues at the source rather than after "validation" Faster PnL triage. Test market issue vs. research assumption vs. implementation bug Smarter portfolio construction trade-offs, informed by research intuition Push back early on unrealistic cost/capacity assumptions in backtests Flag compute-heavy signal designs before they become expensive production rebuilds Backgrounds of future team members? Python Development in a tech driven company, productionizing the Researchers' ideas Coming directly from a competitor in the same asset class and/or trading horizon Programming competition / hackathon winners Top percentile graduates from the world's best STEM universities Want to get closer to the action? Make sure to apply to the link provided! #J-18808-Ljbffr