Quant Engineer

We are looking for an experienced Quant Engineer to join our Trading Core and Risk Tech teams and take ownership of the mathematical models behind our trading and risk infrastructure. With billions in trading volume processed across our systems, accuracy, scalability, and model reliability are essential.
You will develop, backtest, and optimize the quantitative models powering our pricing engines, automated market-making strategies, risk management frameworks, including A/B/C-book optimization, and liquidation logic. Working closely with Core Product Managers and engineering teams, you will apply advanced mathematics, data analysis, and high-performance engineering to turn complex market data into scalable models and proprietary trading advantages.

Responsibilities
Research, design, and prototype quantitative models for pricing, risk management, and market making
Build and maintain robust backtesting frameworks to validate the performance and safety of models before production deployment
Write clear, comprehensive mathematical and algorithmic specifications for Backend Engineers (Trading Core squads)
Cross functional with the R&D and Trading Ops teams
Conduct post-incident deep dives (e.g., after major market gaps or liquidations) to identify algorithm performance gaps and optimize them
Requirements
4+ years of experience as a Quant or Data Scientist
Exceptional knowledge of probability theory, stochastic calculus, time-series analysis, and financial mathematics
Advanced proficiency in Python (NumPy, Pandas, SciPy, SK-Learn, Statsmodels) for data analysis, modeling, and backtesting
Experience with Machine Learning
Deep understanding of market microstructure, order book dynamics, risk metrics (VaR, Expected Shortfall), and margin/liquidation mechanisms
SQL skills and experience working with large-scale historical market data (tick data, order logs)
Strong logical thinking, initiative, and well-developed communication skills
Will be a plus
Experience in CFD, Crypto CEX, Prop Trading Firm, or Hedge Fund
Degree (MSc or PhD preferred) in a highly quantitative field: Mathematics, Physics, Quantitative Finance, Statistics, or Computer Science
Understanding of Asset pricing models (e.g., Black-Scholes, local volatility models, Greeks management)
Knowledge of the MetaTrader platforms (MT4/MT5)
Experience with AI (Claude.io, Copilot, Codex)
We offer
20 paid vacation days per year
10 paid sick leave days per year
Public holidays as per the company’s approved Public holiday list
Medical insurance
Opportunity to work remotely
Professional education budget
Language learning budget
Wellness budget (gym membership, sports gear and related expenses)