Senior Quant Researcher

Senior Quant Researcher

AlgoQuant Asset Management

Dubai (preferred) · London · New York – Reports to Head of Research – Rolling start

About AlgoQuant

• AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across
• 25+ internal and external quantitative trading pods. Founded in 2018, we have evolved into an
• institutional platform combining trading edge with strong governance and advanced technology,
• serving family offices and institutional investors globally.

The role

• We are hiring a Senior Quant Researcher with deep machine learning and deep learning expertise
• to drive the next generation of alpha research at AlgoQuant. This is a senior, high-ownership role
• for someone who has moved beyond applying ML frameworks — you understand why models
• work, where they break, and how to turn raw predictive signal into live, capital-weighted strategy.
• You will lead research into complex, non-linear signal generation across digital asset markets,
• working across spot, derivatives, and on-chain data. You will own research end-to-end: from
• problem formulation and data architecture through to live deployment and performance attribution.
• You will also set the standard for rigour and methodology across the research team.

Responsibilities

• ● Design and deploy advanced ML and DL models for alpha signal generation across digital
• asset markets
• ● Work across the full model stack: feature engineering, architecture selection, training and
• validation regimes, and live signal monitoring
• ● Apply and adapt state-of-the-art techniques — transformer architectures, graph neural
• networks, reinforcement learning, and ensemble methods — to financial prediction
• problems
• ● Build robust, production-grade research pipelines with a rigorous approach to preventing
• lookahead bias, data leakage, and overfitting
• ● Analyse microstructure, order flow, and cross-venue dynamics to enrich feature sets and
• improve signal quality
• ● Collaborate with engineers to move models from research to production infrastructure
• ● Mentor junior researchers and raise the bar for statistical rigour across the team
• ● Contribute to shared research infrastructure, tooling, and datasets
• What we are looking for
• ● Exceptional quantitative background — PhD or equivalent research depth in machine
• learning, statistics, physics, mathematics, or computer science
• ● Genuine expertise in modern ML and DL: transformers, attention mechanisms, graph
• neural networks, boosting algorithms (XGBoost, LightGBM), and reinforcement learning —
• not just familiarity, but hands-on implementation experience
• ● A track record of applying ML in a live, capital-at-risk environment — attributable P&L or
• measurable out-of-sample performance from systematic strategies
• ● Rigorous, almost paranoid approach to model validation — deeply experienced with the
• failure modes of ML in finance: overfitting, regime change, feature leakage, and
• non-stationarity
• ● Strong programming skills — Python required; C++ or Rust a strong plus for production
• performance
• ● Experience working with large, complex, or unconventional datasets; on-chain data
• experience a plus
• ● Self-directed and high-agency — you set your own research agenda and drive it to
• completion
• ● Crypto market exposure a strong plus; intellectual curiosity about digital asset market
• structure essential