Data Scientist (Quantitative Analyst)

Data Scientist (Quantitative Trading) – Dubai

This is a pure quantitative trading role.

We are hiring for a high-performing digital asset trading firm in Dubai. The position is focused on analysing trading and market data to directly improve live trading performance.

If your background is primarily in corporate BI, HR analytics, marketing analytics, or general business reporting, this role will not be suitable.

What You Will Do

• Analyse large-scale trading and market datasets
• Work extensively with time-series financial data
• Evaluate and improve systematic trading strategies
• Design and run controlled experiments (A/B testing) on trading models
• Provide fast, data-driven insights to support live trading decisions
• Identify inefficiencies and performance drivers in trading activity
• Translate complex statistical analysis into practical trading improvements
  
  

Your work will directly influence trading outcomes.

Essential Requirements

Applications without the below experience will not be considered:

• Degree in Mathematics, Physics, Economics, Computer Science, or similar quantitative discipline
• Strong probability and statistics knowledge
• Advanced SQL
• Strong Python for quantitative analysis
• Proficiency in C++
• Proven experience working with time-series data
• Direct exposure to trading, market, or financial datasets
  
  

Highly Desirable

• Experience analysing systematic or algorithmic trading strategies
• Background in quantitative finance
• Understanding of market structure or microstructure
• Experience in crypto or digital asset markets
• Competitive mathematics background
  
  

What’s Offered

• Full visa sponsorship
• Relocation support to Dubai
• Flexible working hours aligned to European markets
• High-performance, research-driven environment
  
  

This role suits candidates who are comfortable in mathematically rigorous environments and motivated by measurable trading performance.

If that describes you, I’d be happy to discuss the opportunity confidentially.