Our client in the Freienbach area is currently looking for a qualified candidate for a Research Analyst position. Your main objective in this position will be to contribute to the development of advanced algorithmic trading strategies using machine learning and agent-based models of financial markets (dynamical systems).
Your main tasks will include:
- Training neural networks for return prediction on various financial markets (e.g. equities, commodities) and conducting experiments to achieve robustness and improve precision;
- Customization of deep learning algorithms including application of Bayesian methods, regularization techniques (e.g. dropouts), pre-training techniques (e.g. autoencoders) and various neural network architectures (e.g. recurrent networks);
- Calibration of stochastically-driven multi-dimensional nonlinear dynamical systems with empirical data and their numerical investigation;
- Marketing support including preparation of marketing materials and presenting in front of internal salesforce and prospective investors.
Requirements
- PhD in mathematics or physics and at least 2 years of post-doctoral research;
- Proven ability to conduct cutting-edge, independent research (such as published journal articles);
- In-depth knowledge of machine learning methods with relevant practical experience;
- Excellent programming skills (e.g. C++, Python, Matlab, R);
- Familiarity with basic concepts and methods in mathematical finance is an advantage;
- Dynamic and result-oriented team player with strong interpersonal skills.