Systematic Machine Learning Quant Researcher
4 weeks ago
Role:
- Conduct quantitative research with PM and other AI quants to develop and back-test different machine learning and statistical models, as well as productionize such models.
- Combine sound financial insights and machine learning techniques to explore, analyze, and harness a large variety of datasets.
- Use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave.
- Apply machine learning to a vast array of datasets
Requirements:
- Masters/PhD degree in Mathematics, Physics, Financial Engineering, Computer Science, Statistics with specialization in Machine Learning
- Experience working with large datasets and machine learning techniques
- Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference.
- Publications at top conferences such as NeurIPS, ICML, ICLR etc. is highly desirable.
- Experience in a high performance language (ideally C++, or similar languages)
- Outstanding performance in any quantitative field or contest (Kaggle, hackathons, olympiads, academic contests etc).
- Experience implementing machine learning algorithms in industry.
- Open to ML quants who are already working within finance or ML quants within tech who are interested to move to finance.
Tell employers what skills you have
TensorFlow
Machine Learning
Sampling
Quantitative Research
Financial Engineering
Physics
Mathematics
PyTorch
Speech Recognition
Python
Anomaly Detection
Statistics
Publications
Data Science
Scientific Computing
C++
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