Prediction Markets Trader: Real-Time, Data-Driven

Trading Interview; Northern (KY); Hybrid; USD 175,000 - 200,000; Full time

Benefits offered by this job

Health insurance

401k plan

Disability insurance

Life insurance

HSA

FSA

Job summary

DRW, a Chicago-based proprietary trading firm, is building a dedicated prediction markets desk. As a Prediction Markets Trader, you will develop, execute, and optimize high-conviction strategies in binary event contracts and manage a live portfolio to target positive expectancy across Polymarket and Kalshi ecosystems.

The role demands strong quantitative reasoning, hands-on evaluation of market signals, and the ability to operate in thin, volatile event-driven environments.

Qualifications

• Bachelor's degree or higher in Quantitative Finance, Statistics, Computer Science, Economics, Mathematics, or equivalent.
• Strong foundation in probability, statistics, time-series analysis, and Bayesian methods.
• Hands-on experience with prediction market platforms (Polymarket and Kalshi APIs) or related domains.
• Genuine, demonstrated interest in prediction markets and active engagement with the space.

Responsibilities

• Monitor and trade active markets in real time across Polymarket and Kalshi.
• Execute strategies including market making with dynamic skew, microstructure arbitrage, cross-platform arb, momentum, and mean-reversion.
• Develop and backtest models using tick data, Bayesian updates, NLP sentiment parsing, and ML for fair-value estimation.
• Collaborate with engineering on low-latency infrastructure and API integrations.

Job description

DRW, a Chicago-based proprietary trading firm, is building a dedicated prediction markets desk. As a Prediction Markets Trader, you will develop, execute, and optimize high-conviction strategies in binary event contracts and manage a live portfolio to target positive expectancy across Polymarket and Kalshi ecosystems.

The role demands strong quantitative reasoning, hands-on evaluation of market signals, and the ability to operate in thin, volatile event-driven environments.