Quantitative Analyst - Prediction Markets
The Role

As Quantitative Analyst, you will drive the research process that underpins our prediction markets trading strategies. You will develop alpha signals, build and validate models, and work closely with our traders and engineers to take research from idea to live deployment. You will own projects end to end - from data ingestion and exploratory analysis through to implementation, testing, and performance monitoring.

We operate across a broad event universe including professional sports, macroeconomics, geopolitics, climate, and financial markets. Research breadth and the ability to develop domain expertise quickly are assets here.
Responsibilities

• Conduct rigorous quantitative research to identify new alpha signals across prediction market categories - sports, macro, political, financial, and environmental events.
• Own the end-to-end research process in close collaboration with the Portfolio Manager: data sourcing and ingestion, exploratory analysis, methodology design, implementation, backtesting, and live performance evaluation.
• Build and maintain data pipelines drawing on alternative and traditional data sources - 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 - tools, libraries, and workflows that make the whole team faster and more rigorous.
• Maintain a systematic review of the academic and practitioner literature on prediction markets, sports analytics, Bayesian forecasting, and related fields.
• Produce clear, structured research outputs - documented methodology, performance attribution, and actionable recommendations - that can be directly used by traders.

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.

Bonus Points For

• Two or more years of experience in a data-driven research environment with a focus on model development and forecasting - though we will consider exceptional candidates at earlier career stages.
• 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 - MCP is actively investing in this area.
• 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.

Who Thrives Here

The best Quantitative Analysts at MCP combine academic rigour with genuine curiosity - they read papers because they want to, follow market resolutions because they are interesting, and build things outside of work because they cannot help it. We value intellectual honesty, the ability to kill your own ideas when the data says so, and the drive to turn good research into production-quality work.

This role is well suited to a researcher who wants to see their work actually trade. Every model you build has a clear path to live deployment, and you will have direct visibility into how your research performs in the market.
How to Apply

Send your CV and a cover letter that demonstrates your genuine engagement with prediction markets and quantitative research. We want to understand what you have built, what you have studied, and how you think about identifying and validating an edge.

Include links to any relevant work: GitHub repositories, research write-ups, Kaggle or competition work, or personal projects. Applications reviewed on a rolling basis. Strong candidates will complete a technical exercise focused on real prediction market data, followed by a research discussion with the team.

Benefits

Compensation

Base salary commensurate with experience, performance-linked bonus. We will discuss specifics with the right candidate.