Quantitative Analyst – Prediction Markets

🔥 3 minutes ago

🌐 Germany, Mexico, +4 more countries – Remote

🇩🇪 Germany – Remote 🇲🇽 Mexico – Remote 🇺🇸 United States – Remote 🇦🇺 Australia – Remote 🇸🇬 Singapore – Remote 🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 17%

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Moreton Capital Partners

WebsiteLinkedInAll Job Openings

2 - 10 employees

💸 Finance

🤖 Artificial Intelligence

Finance • Artificial Intelligence

Moreton Capital Partners is a systematic commodities investment manager that integrates agentic AI, large language models, and advanced machine learning with deep quantitative research, fundamental trading expertise, and institutional-grade risk management to capture inefficiencies across global energy, metals, and agricultural markets. The firm runs a market‑neutral, hypothesis‑driven strategy refined over eight years, with weekly rebalancing, ML-driven analytics for factor and regime risk monitoring, and a focus on interpretable portfolio construction and limited drawdowns. Leadership combines physical commodity trading and agronomy expertise with institutional investment management and operational scalability; products include Cayman master‑feeder share classes and separately managed accounts.

📋 Description

• Conduct rigorous quantitative research to identify new alpha signals across prediction market categories, including sports, macro, political, financial, and environmental events. • Own the end-to-end research process in close collaboration with the Portfolio Manager, including data sourcing and ingestion, exploratory analysis, methodology design, implementation, backtesting, and live performance evaluation. • Build and maintain data pipelines using alternative and traditional data sources, including market microstructure, public resolution data, news and sentiment feeds, sports analytics databases, and fundamental datasets. • Develop and improve models for fair value estimation, calibration analysis, and systematic strategy construction. • Extend and improve MCP's internal research platform, including tools, libraries, and workflows. • Maintain a systematic review of academic and practitioner literature on prediction markets, sports analytics, Bayesian forecasting, and related fields. • Produce documented methodology, performance attribution, and actionable recommendations for traders. • Take research projects from idea through implementation, testing, and performance monitoring, with a path to live deployment.

🎯 Requirements

• Undergraduate or postgraduate degree from a strong institution in data science, computer science, mathematics, statistics, operations research, financial engineering, or a closely related quantitative field. • Strong Python skills: pandas, NumPy, scikit-learn, and experience building backtesting or research frameworks from scratch. • Solid foundation in statistics, probability, time-series analysis, and machine learning — with the ability to apply these rigorously rather than just use libraries. • Demonstrated interest in prediction markets — personal trading, research, protocol analysis, or equivalent engagement. We expect you to know these platforms well. • Ability to work independently and take full ownership of a research workstream, not just execute tasks handed to you. • Two or more years of experience in a data-driven research environment with a focus on model development and forecasting — though exceptional candidates at earlier career stages will be considered. • Familiarity with Polymarket and/or Kalshi platform mechanics, resolution data, and API access. • Experience with NLP, sentiment analysis, or unstructured data processing applied to financial or event-driven contexts. • Comfort with agentic AI frameworks and LLM-based research tooling. • Knowledge of Bayesian methods and their application to probability calibration and forecast updating. • Experience with blockchain data or on-chain analytics tools relevant to decentralised prediction market platforms.

🏖️ Benefits

• Base salary commensurate with experience • Performance-linked bonus