We are seeking a Deep Learning Quantitative Researcher to join one of our systematic client remotely. In this role, you will be at the forefront of developing and implementing advanced deep learning models to drive investment strategies and enhance our quantitative research capabilities.

Responsibilities:

• Conduct research and develop deep learning models for predicting financial markets, including but not limited to time series forecasting, natural language processing (NLP), and image analysis.
• Collaborate with portfolio managers and traders to identify alpha-generating strategies and optimize trading algorithms.
• Stay abreast of the latest developments in deep learning, machine learning, and quantitative finance research, and apply cutting-edge techniques to solve complex financial problems.
• Analyze large datasets to extract meaningful insights and identify patterns that can be used to inform trading decisions.
• Work closely with our technology and data engineering teams to deploy and integrate deep learning models into our trading infrastructure.

Qualifications:

• Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field.
• Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Solid understanding of quantitative finance concepts, including asset pricing, risk management, and portfolio optimization.
• Excellent problem-solving skills and the ability to thrive in a fast-paced, collaborative environment.
• Prior experience working in a quantitative research role at a hedge fund or financial institution is a plus.