Working with a systematic trading group focused on prediction markets spanning sports and real‑world, event‑driven outcomes. The team combines quantitative research, disciplined trading intuition, and strong engineering to capture edge from information flow and uncertainty. They're looking for a Quantitative Trader / Researcher to own modeling, research, and strategy development end‑to‑end.
What You'd Be Working On
• Researching and developing systematic trading strategies for prediction markets
• Modeling probabilities, information dynamics, and market inefficiencies
• Identifying alpha driven by behavioral bias, timing, or structural features
• Backtesting, validating, and monitoring strategies in live trading
• Working closely with engineers to deploy and iterate on production strategies
Ideal Background
• Strong foundation in probability, statistics, optimization, or machine learning
• Experience in trading, sports betting, prediction markets, or financial markets
• High proficiency in Python
• Comfort working with noisy, sparse, and real-time data
• Intellectual curiosity around markets, incentives, and information efficiency
Why This Role
• Prediction markets treated as a first-class quantitative trading problem
• High ownership over research direction and strategy lifecycle
• Tight feedback loop between research, execution, and PnL
• Competitive compensation with real upside tied to performance
• Exposure to sports and real-world event-driven markets at scale
