Traders - Prediction Markets

Moreton Capital Partners

3h•Remote

About The Position

Moreton Capital Partners (MCP) is a CFTC regulated systematic, technology-first investment manager trading across commodities, alternative markets, and emerging data-rich asset classes. We combine quantitative modelling, agentic AI, and deep domain expertise to build strategies with durable, uncorrelated alpha. Prediction markets are one of the firm's high-conviction growth areas. We are building a dedicated strategy, partnering and trading on world leading event contract platforms, and are hiring global traders to join the team and run a small live book from day one.

Requirements

Direct, hands-on experience trading on Polymarket and/or Kalshi — via personal accounts, proprietary systems, or professional roles. We expect specifics: markets traded, strategies used, edges identified.
Strong Python skills: pandas, NumPy, backtesting frameworks, and API integrations built from scratch.
Solid foundation in probability, statistics, time-series analysis, and Bayesian inference.
Genuine, demonstrable engagement with the prediction markets ecosystem. This is a hard filter: we will ask for specifics about recent resolutions, platform mechanics, and structural observations.
Undergraduate or higher degree in a quantitative discipline, or equivalent demonstrated ability.

Nice To Haves

A live profitable track record in prediction markets, options, or event-driven strategies — even at personal scale.
Experience with blockchain and DeFi tooling: Polygon RPC, USDC wallet management, ethers.js or equivalent.
Familiarity with low-latency execution, FIX protocol, or Web3 API infrastructure.
Domain depth in high-volume event categories: professional sports analytics, macroeconomics, geopolitics, climate.
Interest in or experience with agentic AI applied to trading — an active investment area at MCP.

Responsibilities

Monitor and manage live positions across Polymarket (CLOB, Gamma, Subgraph APIs) and Kalshi (REST, WebSocket) throughout the trading day.
Execute strategies including: dynamic market making with real-time skew adjustment, order-flow and book imbalance exploitation, cross-platform pricing arbitrage, news and event momentum, and mean-reversion on statistically related contract pairs.
Build and backtest quantitative models using historical tick data, Bayesian probability frameworks, NLP-driven news parsing, and ML-based fair value estimation.
Collaborate with engineering on execution infrastructure — API integrations, order routing, position monitoring, and anomaly detection.
Maintain thorough post-trade analysis: attribution, model performance, slippage, and strategy decay monitoring.
Contribute ideas to the broader research agenda — prediction markets sit within MCP's wider effort to apply agentic AI and multi-signal frameworks to event-driven alpha.