Quantitative Analyst – Prediction Markets

This is a fully remote position, open to applicants in Germany, +5 more countries.

📋 Description

• Lead the research initiatives that form the foundation of trading strategies in prediction markets.

• Create alpha signals, develop and validate models, and collaborate closely with traders and engineers to transition research from concepts to live implementation.

• Manage projects comprehensively — from data collection and exploratory analysis to implementation, testing, and performance assessment.

• Perform thorough quantitative research to discover new alpha signals in various prediction market domains — including sports, macroeconomic, political, financial, and environmental events.

• Take responsibility for the complete research process in close partnership with the Portfolio Manager: data sourcing and ingestion, exploratory analysis, methodology design, implementation, backtesting, and live performance evaluation.

• Construct and maintain data pipelines utilizing both alternative and traditional data sources — encompassing market microstructure, public resolution data, news and sentiment feeds, sports analytics databases, and fundamental datasets.

• Develop and refine models for fair value estimation, calibration analysis, and the construction of systematic strategies.

• Enhance and expand MCP's internal research platform — including tools, libraries, and workflows that increase the efficiency and rigor of the entire team.

• Conduct a systematic review of academic and practitioner literature related to prediction markets, sports analytics, Bayesian forecasting, and similar fields.

• Generate clear, structured research outputs — including documented methodologies, performance attributions, and actionable recommendations — that traders can directly utilize.

⛳️ Requirements

• Bachelor's or master's degree from a reputable institution in data science, computer science, mathematics, statistics, operations research, financial engineering, or a related quantitative discipline.

• Proficient in Python: including libraries such as pandas, NumPy, scikit-learn, and experience in building backtesting or research frameworks from the ground up.

• Strong foundation in statistics, probability, time-series analysis, and machine learning — with the capability to apply these concepts rigorously rather than merely utilizing libraries.

• Proven interest in prediction markets — whether through personal trading, research, protocol analysis, or similar involvement. Familiarity with these platforms is essential.

• Ability to work autonomously and take complete ownership of a research workstream, rather than just executing assigned tasks.

• A minimum of two years of experience in a data-centric research environment focusing on model development and forecasting — although exceptional candidates at earlier career stages will also be considered.

• Understanding of Polymarket and/or Kalshi platform mechanics, resolution data, and API access.

• Experience in NLP, sentiment analysis, or processing unstructured data in financial or event-driven contexts.

• Comfort with agentic AI frameworks and LLM-based research tools — MCP is actively investing in this domain.

• Knowledge of Bayesian methods and their application in probability calibration and forecast updating.

• Experience with blockchain data or on-chain analytics tools pertinent to decentralized prediction market platforms.

🏝️ Benefits

• Competitive base salary aligned with experience and a performance-based bonus.