Uncover market patterns through advanced statistical research, machine learning, and data analysis, developing predictive trading models and strategies while collaborating with traders and technology specialists.

What You'll Do:

1. Analyze global financial markets and large datasets to uncover meaningful patterns.
2. Develop predictive models and systematic trading strategies.
3. Apply statistical analysis, data mining, and machine learning techniques to financial data.
4. Research and test new trading hypotheses using rigorous quantitative methods.
5. Collaborate closely with trading teams to optimize strategies and improve performance.
6. Contribute to sophisticated electronic trading strategies through innovative research.
7. Develop research tools and supporting software in a Linux environment.
8. Continuously investigate new approaches to advance quantitative and machine learning techniques.

Your Responsibilities Will Include:

1. Collecting, cleaning, analyzing, and interpreting large financial datasets.
2. Developing statistical models within a trading environment.
3. Applying forecasting and data-mining techniques including linear and non-linear regression, neural networks, and support vector machines.
4. Creating and refining profitable predictive trading models.
5. Evaluating strategy performance and identifying opportunities for optimization.
6. Programming research solutions usingC++ , alongside Python, R, or Matlab.
7. Working with technology and business teams to translate research into practical trading applications.
8. Communicating research findings and insights clearly to technical and non-technical stakeholders.

Why Join Us:

1. Work at the intersection ofquantitative research, machine learning, and electronic trading .
2. Tackle challenging problems involving complex markets and massive datasets.
3. See your research directly influence trading strategies and measurable performance.
4. Collaborate with talented researchers, traders, technologists, and business specialists.
5. Explore advanced statistical and machine learning techniques in a real-world trading environment.
6. Have the opportunity to push the boundaries of how machine learning is applied to financial markets.

About You:

1. Master's or PhD inStatistics, Physics, Mathematics , or a related quantitative discipline.
2. Proven experience developing statistical models in a trading environment.
3. Demonstrated success developing profitable trading strategies.
4. Strong C++ programming skills within a Linux environment.
5. Strong knowledge of forecasting, data mining, and statistical modelling techniques.
6. Experience working with large datasets.
7. Familiarity with Python, R, or Matlab and supporting development skills.
8. Strong analytical and creative problem-solving abilities.
9. Self-motivated, proactive, and comfortable conducting independent research.
10. Strong written and verbal English communication skills.
11. Collaborative mindset with a genuine interest in advancing machine learning within trading.

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