Responsibilities

• Work closely with traders and quant research team to gathering actual requirements on financial data acquisition and manipulation to drive the ongoing analytical products' refinement deliverables.
• Brainstorm new business initiatives, technical architecture design and the feasibility study with engineering teams leveraging the latest data science and analytical technologies.
• Build and support data visualisation and automated report engines to meet business needs.
• Perform data anslysis using statistical modeling and machine learning methodlogies to capture the relevant financial data and generate predictive models for strategies execution.
• Define document process and methodologies to ensure the data products' scalability and knowledge sharing within engineering teams.

Requirements:

• Bachelor or Master degree in quantitative finance, mathematics and statistics, computer science or other relevant disciplines.
• Minimum 3 years of professional experience in financial engineering or quantitative investment functions, coming from sell side or buy side sector.
• Expertise in data science libraries in Python, not limited to PyTorch, TensorFlow, Numpy, Pandas or Keras.
• Outstanding presentation skills in liaising with senior directors, research, trading desks, data engineers, technical product and support teams.
• Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms of processing alternative financial datasets.

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