AlgoQuant Asset Management
Dubai (preferred) · London · New York – Reports to Head of Research – Rolling start
About AlgoQuantAlgoQuant 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 roleWe are hiring Quant Trade Researchers at both junior and senior levels to design, test, and deploy systematic trading strategies across digital asset markets. You will generate ideas from first principles, validate them with rigorous statistics, and ship signals into live capital, in weeks, not quarters. You will work directly with portfolio managers and engineers who move at your pace.
This role is for people who live in data, mathematics, and code, relentlessly analytical, hungry for P&L, and happiest with a terminal and an unsolved problem in front of them. You will own research end-to-end, from first principles to production, and the work rewards raw firepower paired with the discipline to turn it into a signal.
Responsibilities- Generate and test systematic trading hypotheses across spot, derivatives, and on-chain markets
- Build, validate, and maintain live alpha signals and execution models
- Run rigorous backtests, guarding against lookahead, data-leakage, and overfitting
- Analyse microstructure, order flow, and cross-venue dynamics to improve portfolio construction
- Collaborate with engineers to move research from notebook to production
- Monitor live strategy performance and iterate quickly on results
- Contribute to shared research infrastructure, tools, datasets, and code
- Exceptional mathematical, statistical, or scientific pedigree Olympiad medallists, PhDs, and top-decile graduates in maths, physics, computer science, or equivalent
- Deep understanding of statistical learning, classical machine learning, and deep learning; strong experience implementing a wide range of models, including boosting algorithms, transformers, and reinforcement learning.
- Strong programming ability, Python required, C++ or Rust a plus
- Relentless curiosity and high agency, someone who cannot walk away from an unsolved problem
- Comfort owning research end-to-end without hand-holding
- For junior candidates: a research track record strong enough that we would hire on potential, papers, Kaggle wins, competitive programming results, or systematic trading experiments
- For senior candidates: a live, attributable track record in systematic trading; crypto exposure a strong plus
- A genuinely paranoid eye for data quality and bias, not comfortable until every result has a clear explanation
- A genuine love for the subject, not just the paycheque
Skills Required
- Exceptional mathematical, statistical, or scientific pedigree (Olympiad medallist, PhD, top-decile graduate)
- Deep understanding of statistical learning, classical machine learning, and deep learning
- Experience implementing models including boosting algorithms, transformers, and reinforcement learning
- Strong programming ability in Python
- Experience with C++ or Rust
- Ability to run rigorous backtests and guard against lookahead, data-leakage, and overfitting
- Experience shipping research from notebook to production and collaborating with engineers
- For junior candidates: strong research track record (papers, Kaggle wins, competitive programming, systematic trading experiments)
- For senior candidates: live, attributable track record in systematic trading (crypto exposure a strong plus)
- A paranoid eye for data quality and bias
What We Do
At AlgoQuant, we're building the future of digital asset management; grounded in rigorous research, world-class technology and a relentless focus on performance. We began as a proprietary trading firm, developing sophisticated algorithmic strategies and operating in some of the most complex and fast-moving markets. That DNA remains at our core, but today we are evolving into a fully remote, globally distributed Investment Management business. This transformation reflects a broader ambition: to scale our edge, deliver institutional-grade results, and set new standards for the industry. Our quantitative environment is built to empower innovation, combining vast data capabilities, disciplined model development, and highly automated execution. Risk is embedded in every layer of our thinking, with robust measurement, control, and scenario analysis integrated into our systems and decision-making. Technology is not just a tool for us, it’s a core competency and a competitive advantage.
