Junior Quantitative Researcher - Deep Learning (Time Series)

Requirements

• Bachelors, Masters or PhD in a technical field – Engineering, Statistics, Computer Science, Mathematics, Physics (or a related subject), graduate(d) during Jul 2023 - Jul 2027
• Deep learning experience is required: hands-on work with neural network architectures (e.g., RNNs, LSTMs, Transformers, TCNs, or similar) applied to sequential or time series data — through research, working projects, competitions, or internships
• Programming skills: Strong Python programming experience, including familiarity with DL frameworks (PyTorch and/or TensorFlow); C++ knowledge is a plus
• Experience handling large-scale datasets efficiently — data pipelines, batching, and training at scale (GPU experience is a plus)
• Solid foundation in math and statistics, with the ability to translate real-world, noisy, high-dimensional problems into mathematical/DL models
• Prior exposure to time series-specific challenges (non-stationarity, autocorrelation, forecasting, sequence modeling) is a strong plus
• Financial experience is not a requirement
• Willing to communicate in English at the technical interviews
• Please note: If you apply to multiple roles, you may be asked to complete multiple coding challenges and interviews.

Apply on Akuna Capital's site