Prediction Markets Trader - Live P&L, Edge-Driven

Moreton Capital Partners; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Moreton Capital Partners seeks a Trader to manage a live portfolio of prediction market positions and to develop a suite of strategies. You will work with a Portfolio Manager and access quant analysts to refine the edge while staying execution-focused on live P&L.

The role emphasizes hands-on trading on Polymarket and Kalshi, building quantitative models, and close collaboration with engineering for execution infrastructure. A strong track record in related markets is valued.

Qualifications

• Strong Python skills: pandas, NumPy, backtesting frameworks.
• Experience trading on Polymarket and/or Kalshi with edge identification.
• Genuine engagement with the prediction markets ecosystem and platform mechanics.
• Undergraduate or higher degree in a quantitative discipline or equivalent.

Responsibilities

• Monitor and manage live positions across Polymarket and Kalshi throughout the trading day.
• Execute strategies including market making, order-flow exploitation, cross-platform arbitrage, and momentum-based moves.
• Build and backtest quantitative models using historical tick data and Bayesian methods.
• Collaborate with engineering on execution infrastructure and APIs.
• Maintain post-trade attribution, model performance, and decay monitoring.
• Contribute ideas to the broader research agenda for event-driven alpha.

Skills

Python

Pandas

NumPy

Backtesting

APIs

Probability

Time-series

Bayesian inference

Education

Undergraduate or higher degree in a quantitative discipline

Tools

Polymarket

Kalshi

FIX protocol

Web3/API infra

Job description

Moreton Capital Partners seeks a Trader to manage a live portfolio of prediction market positions and to develop a suite of strategies. You will work with a Portfolio Manager and access quant analysts to refine the edge while staying execution-focused on live P&L.

The role emphasizes hands-on trading on Polymarket and Kalshi, building quantitative models, and close collaboration with engineering for execution infrastructure. A strong track record in related markets is valued.