Junior Quantitative Researcher - Deep Learning (Time Series)

You will develop trading strategies with statistical and deep learning methods, design portfolio construction optimization algorithms, build quantitative models of market behavior, and advance research initiatives involving large-scale time series data. You will work with neural networks, Python, deep learning frameworks, data pipelines, and large-scale training workflows.

Responsibilities

• Develop trading strategies using statistical and deep learning technologies
• Design and implement optimization algorithms for portfolio construction
• Develop quantitative models describing market behavior
• Advance existing initiatives and explore new research topics

Requirements

• Bachelor's, master's, or PhD in engineering, statistics, computer science, mathematics, physics, or a related technical field
• Graduate between July 2023 and July 2027
• Hands-on deep learning experience with neural network architectures applied to sequential or time series data
• Strong Python programming experience with PyTorch and/or TensorFlow
• Experience handling large-scale datasets efficiently
• Strong foundation in mathematics and statistics
• English communication skills for technical interviews
• C++ knowledge is a plus
• GPU experience is a plus
• Prior exposure to time series challenges is a plus

Benefits

• Happy hours
• Free drinks and fresh fruits
• Team events
• Social club events