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Lead capital allocation for a multi-asset fund, focusing on dynamic asset allocation, risk budgeting, and cross-asset research to optimize a diversified portfolio.
Job Description
As we expand our footprint from a crypto-native foundation into a sophisticated global multi-asset fund, we are seeking a Portfolio Manager (PM) to lead our top-level capital allocation. You will not just manage a book; you will design and execute the "Ensemble Strategy" that dictates how capital flows between digital assets, traditional macro markets, and emerging prediction venues. Your mission is to engineer a "Weather-Proof" portfolio that extracts idiosyncratic alpha from disparate markets while maintaining a strictly controlled risk profile.
Responsibilities- Dynamic Asset Allocation: Oversee the deployment of capital across five core sleeves: Crypto, Commodities, FX, Equities, and Prediction Markets.
- Ensemble Optimization: Build and maintain quantitative frameworks (Risk Parity, Mean-Variance, or Bayesian models) to determine optimal weights based on real-time volatility and correlation.
- Regime-Based Hedging: Utilize Prediction Markets and FX to hedge tail risks and macro shifts impacting the core Equity and Crypto portfolios.
- Risk Budgeting: Define and monitor VaR, Stress Tests, and Drawdown limits for individual strategy sleeves.
- Cross-Asset Research: Identify "Lead-Lag" relationships—e.g., how movement in the US Dollar (DXY) or Treasury yields impacts Crypto liquidity and Commodity pricing.
- Experience: 5-10 years in a Quantitative PM or Senior Allocation role at a multi-strat hedge fund, prop shop, or family office.
- Multi-Asset Mastery: Proven track record managing risk across at least three of our five core asset classes. Experience in Prediction Markets (Polymarket, Kalshi) or Event-Driven Trading is a significant plus.
- The Stack: Expert proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow) and SQL/KDB+.
- Quantitative Depth: Mastery of portfolio construction mathematics, including covariance matrix estimation and L^2 regularization.
- Education: Advanced degree (Masters/PhD) in Mathematics, Physics, Computer Science, or Financial Engineering.
- The Aggregator: You don't just look for "good trades"; you look for how trades fit together to improve the fund's overall Information Ratio.
- The Risk-First Thinker: You understand that in a levered multi-asset environment, correlation is the silent killer.
- The Adaptable Architect: You are comfortable transitioning from the 24/7 volatility of Crypto to the structural nuances of the Commodities curve and the binary outcomes of Prediction Markets.
Top Skills
Kdb+
Numpy
Pandas
Python
PyTorch
SQL
TensorFlow
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