Design and implement sophisticated client segmentation models, automated recommendation engines, and dynamic pricing frameworks.
Build, back-test, and deploy intelligent algorithms and predictive models to support automated execution and market-making strategies across FX products.
Architect and deliver robust, low-latency analytical models directly into production-ready engines.
Collaborate closely with the FX Sales team and maintain continuous communication with data science and quant teams across geographies.
Requirements
2–5 years of proven experience as a Data Scientist, Quantitative Researcher, or Algorithmic Trading Developer within financial markets.
Master’s or Bachelor's degree in Physics, Mathematics, Engineering, Statistics, Computer Science, or a deeply quantitative field.
Strong mathematical foundations with valuable knowledge of stochastic processes, numerical methods, optimization, and machine learning architectures.
Solid understanding of financial markets and derivatives.
Advanced mastery of Python, PySpark, and SQL.
Hands-on experience with Machine Learning libraries (TensorFlow, PyTorch, scikit-learn) and cloud infrastructure within Amazon SageMaker.