We're looking for a Quant Trader to run a low-risk, market-neutral/arbitrage book and build the tools to trade it efficiently. This is a hands-on role for someone who's as comfortable writing production grade code as they are managing risk on a live book. You'll own the full loop from strategy logic to execution to monitoring with eventual direct P&L; responsibility.
What You'll Do
Manage a systematic, low-risk arbitrage book (e.g., cash-futures, cross-exchange, or relative-value strategies)
Design, build, and maintain your own pricing, signal, and execution infrastructure
Continuously monitor risk, slippage, and book performance; refine strategies based on live data
Automate manual processes and improve system reliability/latency
Collaborate with risk and infra teams to ensure the book stays within defined limits
What We're Looking For
Solid coding ability (Python and/or C++) you should be able to ship clean, productive, production-ready code independently
Solid grounding in market microstructure, arbitrage, or relative-value strategies
Experience managing real trading risk, or solid quantitative/finance background with a demonstrated ability to trade
Comfort working with large datasets, backtesting frameworks, and low-latency systems
A bias toward automation and process efficiency over manual intervention
Nice to Have
Experience with equities/futures required
Background in a prop trading firm, hedge fund, or market-making desk