Traders — Prediction Markets
About Moreton Capital Partners
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.
The Role
As a Trader, you will execute and actively manage a live portfolio of prediction market positions. You will develop and own a suite of strategies, reporting into a Portfolio Manager and accessing quant analysts to continuously refine our edge.
This is an execution-first role: you are on the tools, managing live positions, and responsible for real P&L. We are equally interested in proven practitioners and sharp, self-directed candidates earlier in their careers who can demonstrate they have already been doing this seriously on their own.
Key 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.
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.
Bonus Points For
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.
Who Thrives Here
The Trader role at MCP suits someone who runs hot on markets — who monitors Polymarket and Kalshi not because they have to, but because they cannot help it. If you have been building personal models, studying resolution patterns, or finding edges in thin markets on your own time, you are exactly who we want to talk to. We are as interested in exceptional self-starters earlier in their careers as we are in experienced professionals.
How to Apply
Send your CV and a cover letter that goes beyond generic interest. Tell us specifically: markets you have traded, strategies you have run, edges you have found, and what you see as the clearest structural opportunities available today on Polymarket or Kalshi.
Include links to any relevant work — GitHub, personal research, or portfolio evidence. Applications reviewed on a rolling basis. Strong candidates will progress through a technical screen, strategy discussion, and a live modelling or coding exercise.
Performance-linked compensation. Details discussed at the offer stage.