Quantitative Analyst – Prediction Markets

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

📋 Description

• Perform in-depth quantitative research to uncover new alpha signals across various prediction market categories, such as sports, macroeconomic, political, financial, and environmental events.

• Oversee the entire research process in close partnership with the Portfolio Manager, covering data sourcing and ingestion, exploratory analysis, methodology design, implementation, backtesting, and evaluation of live performance.

• Create and sustain data pipelines utilizing both alternative and traditional data sources, including market microstructure, public resolution data, news and sentiment feeds, sports analytics databases, and fundamental datasets.

• Enhance and refine models for fair value estimation, calibration analysis, and systematic strategy development.

• Expand and upgrade MCP's internal research platform, which encompasses tools, libraries, and workflows.

• Conduct a systematic review of academic and practitioner literature on prediction markets, sports analytics, Bayesian forecasting, and related disciplines.

• Generate documented methodologies, performance attribution, and actionable insights for traders.

• Advance research projects from conception through implementation, testing, and performance monitoring, ultimately leading to live deployment.

⛳️ Requirements

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

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

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

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

• Capability to work autonomously and take full responsibility for a research workstream, rather than just executing assigned tasks.

• A minimum of two years of experience in a data-driven research setting focused on model development and forecasting; however, outstanding candidates in earlier career stages may be considered.

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

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

• Comfort with agentic AI frameworks and research tools based on large language models (LLMs).

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

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

🏝️ Benefits

• Base salary aligned with experience

• Performance-based bonus