AlgoQuant

FinTech

SeniorQuantResearcher

₹45–75L ~AI est. Remote Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Quant Researcher at AlgoQuant. Skills: Machine learning, Deep learning, Alpha generation, Quantitative research. Design ML models. Deploy ML models”

What You'll Achieve.

Turn predictive signal into strategy

Industry & Context.

FinTech
Problems you'll solve

Complex non-linear signal generation

What They're Looking For.

Must Have

PhD or equivalent research depth, Machine learning expertise, Deep learning expertise, Hands-on implementation experience, Live, capital-at-risk environment experience, SQL proficiency, 5+ years Python experience

Nice to Have

PhD preferred, Experience with unconventional on-chain data, C++ or Rust a plus, Cloud platform certs

What You'll Do.

Generate alpha signals

Build research pipelines

Prevent lookahead bias

Analyse microstructure

Analyse cross-venue dynamics

Improve signal quality

Collaborate with engineers

Move models to production

Mentor junior researchers

Raise statistical rigour

Contribute to infrastructure

Contribute to tooling

Contribute to datasets

How You'll Work.

Team & Collaboration

With engineers; With research team

Process & Methodology

End-to-end research ownership

Full Job Description

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 t

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