AlgoQuant
FinTech
SeniorQuantResearcher
Neural analysis suggests this role is
optimal for Senior candidates.
“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.
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
Applying for this Senior Quant Researcher role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Greenhouse
- Create a Greenhouse profile before applying — it saves time across multiple applications.
- Upload your resume as a PDF; the parser handles it better than Word.
- Answer all knockout questions carefully — wrong answers auto-reject before a human sees you.
- Enable email notifications to track application status in real time.
ANONYMOUS · UNFILTERED
What do employees actually say about AlgoQuant?
Real rants from real employees. Read before you apply.