Data Scientist

We are looking for a Data Scientist to become the data-driven backbone of our Trading Core and Risk Tech squads. In a high-frequency trading environment processing billions in volume, success is defined by precision.

In this role, you will research, model, and validate the core data-driven models that drive our pricing engines, automated market-making algorithms, risk management frameworks (A/B/C-book optimization), and liquidation mechanics. You will sit at the intersection of statistics, data science, and high-performance software engineering, working directly with Core Product Managers and engineering teams to turn complex financial data into proprietary algorithmic advantages.

Responsibilities

• Research, design, and prototype behavioral, risk, and toxicity-scoring models for client and partner-flow segmentation
• Build backtesting and monitoring frameworks to validate models, signals, and hypotheses across data of varying granularity
• Detect early risk signals, anomalies, and regime shifts in market and client behavior, including probability of critical capital loss
• Develop explainable risk signals and labels for the R&D team, and long-term client value/risk models with forecasting
• Conduct research and hypothesis-testing on client economics, flow quality, and model performance

Requirements

• 3+ years of experience as a Data Scientist / Quantitative Researcher 
• Exceptional knowledge of probability theory, statistics, time-series analysis, and financial mathematics
• Advanced proficiency in Python (NumPy, Pandas, SciPy, Scikit-learn, Statsmodels) for data analysis, modeling, and backtesting
• Solid 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, Statistics, Quantitative Finance, 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)

Role mission

About the role:
We are looking for a brilliant Quantitative Analyst to become the mathematical backbone of our Trading Core and Risk Tech squads. In a high-frequency trading environment processing billions in volume, success is defined by precision. In this role, you will design, backtest, and optimize the core mathematical models that drive our pricing engines, automated market-making algorithms, risk management frameworks (A/B/C-book optimization), and liquidation mechanics. You will sit at the intersection of advanced mathematics, data science, and high-performance software engineering, working directly with Core Product Managers and engineering teams to turn complex financial data into proprietary algorithmic advantages.

1. Role Mission
To design and optimize the mathematical, statistical, and algorithmic models that power the trading engine. The global need is to maximize company profitability (P&L optimization via smart hedging and internalization), ensure bulletproof risk management during extreme market volatility, and eliminate losses from toxic flow or latency arbitrage.

Requirements soft skills

Mathematical Rigor: A meticulous mindset that doesn't rely on guesswork—every hypothesis must be proven with statistical data.

Collaboration & Communication: The ability to explain complex mathematical abstractions in simple, actionable terms to Product Managers and Software Engineers.

Agility & Focus: Ability to maintain logical clarity and deliver precise solutions under pressure, especially when analyzing market incidents or anomalies.

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).

Collaboratively monitor production model performance with the Dealing and Trading Ops teams, tweaking mathematical parameters when market regimes change.

Conduct post-incident deep dives (e.g., after major market gaps or liquidations) to identify algorithm performance gaps and optimize them.

Will be a plus

Hands-on experience with C++ or Rust for low-latency execution and high-performance computing.

Deep understanding of Options pricing models (e.g., Black-Scholes, local volatility models) and Greeks management.

Experience in building or optimizing algorithms specifically for MetaTrader (MT4/MT5) bridging infrastructure.