About the Role
Cambridge Quantum Computing is looking to hire a Machine Learning Scientist for its Machine Learning unit. The role involves applying state-of-the-art Machine Learning and specifically, Deep Learning techniques to financial time-series forecasting on diverse sources of data. The successful candidate will join the London office and will be working in a highly dynamic, research-focused group, teaming up with senior members of the team and reporting directly to the project head.
Responsibilities
* Stay on par with the latest research literature in the ML field
* Analyse high resolution financial data to identify statistically significant trading patterns and extract predictive features.
* Train state-of-the‑art DL algorithms to learn profitable trading strategies.
* Prototype and implement new ML ideas in CQC’s proprietary R&D software platform.
* Deploy ML/DL strategies in the most competitive financial markets.
Key Requirements
* A master’s degree in Machine Learning or Computational Statistics from a top‑tier University, or a degree in a quantitative discipline (Math, Physics, Computer Science) and relevant experience.
* Proficiency with Python 3 and its scientific/ML libraries such as Numpy, Pandas, Scikit‑Learn, Tensorflow and Keras.
* Knowledge of Deep Learning fundamentals applied to a relevant domain (Computer Vision, Speech Recognition, Natural Language Processing etc.).
* A Passion for approaching complex problems with the goal to design and deliver novel practical solutions.
Desirable Skills
* A PhD in relevant discipline and a track record of scientific publications.
* Hands‑on experience in the development and deployment of ML systems gained in a commercial or research environment.
* Familiarity with time‑series processing and feature extraction (particle filtering, state‑space models, wavelet transforms, dimensionality reduction, etc.).
* Experience in collaborative software development and version‑control‑systems (git).
All candidates must be eligible to live and work in the UK.
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