Trading – Quantitative Researcher

Quantitative Researcher - AlgoQuant Asset Management Preferred Locations: London, New York, or Dubai (fully remote) About AlgoQuant Asset Management AlgoQuant Asset Management is an ambitious and pioneering multi-strategy crypto asset manager. For over five years, we have operated as a proprietary trading firm, making tactical allocations to both internal and external quantitative trading teams. In 2024, Michael Ashby joined as CEO, bringing expertise from leading Point72’s digital assets division across quant, venture, and macro trading. With a strengthened executive team, we are transitioning into an investment management firm, managing external capital while leveraging our technology, risk management expertise, and deep market experience. At AlgoQuant, we believe in the power of both internal and external teams, casting a wide net for new ideas, identifying world-class talent, and diversifying our alpha sources. Role Overview As a Quantitative Researcher focused on alpha and signal generation, you will be at the core of our strategy development efforts. Your primary responsibility will be to discover, validate, and iterate on predictive signals across digital asset markets. This role is deeply research-driven and requires a strong grasp of machine learning techniques, statistical rigor, and an experimental mindset. You will work independently or in small teams to drive innovation in alpha research, supported by experienced technologists and portfolio managers. The ideal candidate combines technical depth with curiosity, persistence, and a passion for uncovering hidden structure in complex datasets.

Key Responsibilities

• Conduct original quantitative research aimed at identifying and validating alpha signals in crypto markets.
• Build and refine ML/DL-based models to detect predictive patterns in noisy, high-dimensional time series data.
• Develop robust methods for signal construction, feature engineering, and data transformation.
• Use advanced validation techniques (e.g., walk-forward analysis, ensembling, cross-validation) to prevent overfitting and ensure signal robustness.
• Work with raw and alternative datasets, transforming them into actionable research insights.
• Collaborate closely with the Portfolio Manager and other researchers to iterate on ideas and improve signal quality.
• Document research clearly and communicate findings effectively to a technical and non-technical audience.

Minimum Qualifications

• Advanced degree (PhD or MSc) in a quantitative discipline such as Computer Science, Mathematics, Physics, Statistics, or Engineering from a top-tier institution.
• At least 2 years of hands-on experience designing and implementing machine learning or deep learning models in a research or production context.
• Exceptional coding skills in Python, including experience with libraries such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
• Strong understanding of overfitting avoidance techniques: regularization, cross-validation, early stopping, feature selection, blending, stacking, etc.
• Demonstrated ability to work independently and explore ideas with scientific rigor and efficiency.
• Strong analytical and statistical intuition, with a focus on extracting signal from noisy data.

Preferred Qualifications

• Prior experience researching alpha signals in digital assets or traditional financial markets.
• Familiarity with market microstructure, exchange data, or alternative data sources relevant to crypto.
• Experience working with large-scale, unstructured, or high-frequency data.
• Knowledge of signal performance metrics, backtesting frameworks, and validation best practices.
• Familiarity with high-performance computing environments or distributed research workflows.
• Strong publication record or evidence of independent research projects in machine learning or quantitative modeling.

Why Join Us

• Be part of a high-caliber, globally distributed team pushing the frontiers of alpha research in crypto.
• Join a firm that blends the agility of a prop trading shop with the structure and ambition of an asset manager.
• Enjoy the flexibility of a fully remote environment with the infrastructure to support world-class collaboration.
• Make meaningful contributions to live trading strategies from day one and grow in an entrepreneurial, performance-oriented culture.

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