Traders - Prediction Markets

Moreton Capital Partners; United States; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Performance-linked compensation

Job summary

Moreton Capital Partners in the United States is seeking a Trader to manage a live portfolio of prediction market positions and develop edge-driven strategies.

You will build and backtest quantitative models, collaborate with a Portfolio Manager and quant analysts, and handle execution with real-time APIs on Polymarket and Kalshi.

We value self-starters and both experienced professionals and ambitious early-career traders who have demonstrated independent work.

Qualifications

• Direct, hands-on experience trading on Polymarket and/or Kalshi; markets traded, strategies used, edges identified.
• Strong Python skills: pandas, NumPy, backtesting frameworks, and APIs built from scratch.
• Solid foundation in probability, statistics, time-series analysis, and Bayesian inference.
• Genuine engagement with the prediction markets ecosystem; be ready to discuss platform mechanics and resolutions.
• Undergraduate or higher degree in a quantitative discipline, or equivalent demonstrated ability.

Responsibilities

• Monitor and manage live positions across Polymarket and Kalshi throughout the trading day.
• Execute strategies including dynamic market making, order-flow and book imbalance exploitation, and cross-platform pricing arbitrage.
• Build and backtest quantitative models using historical tick data and Bayesian frameworks.
• Collaborate with engineering on execution infrastructure—API integrations, order routing, position monitoring.
• Maintain post-trade analysis: attribution, model performance, slippage, strategy decay monitoring.
• Contribute ideas to the broader research agenda for event-driven alpha.

Skills

Trading on Polymarket/Kalshi

Python scripting

Probability & statistics

Time-series analysis

NLP / data parsing

Education

Bachelor's or higher in a quantitative field

Tools

Python

Pandas

NumPy

Backtesting frameworks

API integrations

Job description

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.

Traders — Prediction Markets

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

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

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.

Benefits

Performance-linked compensation. Details discussed at the offer stage.