My client are a $20bn systematic hedge fund looking at expanding their X-asset deep learning research in Paris. You would have the opportunity to build a verifiable track record.
Key Responsibilities:
- Develop and apply state-of-the-art deep learning techniques to identify patterns and trends in financial markets.
- Collaborate with domain experts to explore, clean, and preprocess large-scale structured and unstructured datasets.
- Build and backtest systematic trading strategies, ensuring robustness and scalability.
- Conduct research into novel methodologies, keeping the fund at the forefront of deep learning innovation.
- Communicate findings and recommendations clearly to technical and non-technical stakeholders.
Qualifications:
- Masters PhD in a quantitative discipline (e.g., Computer Science, Mathematics, Physics, Statistics, or related field).
- Strong programming skills in Python, R, or C++ with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
- Proficiency in statistical analysis and optimization techniques.
- Familiarity with financial market data and concepts.
- 2+ years in quantitative research, data science, or a related field, ideally within finance.
- Ability to frame complex problems in a systematic way and propose innovative solutions.
If there is interest, please apply directly or reach out to harry.moore(at)selbyjennings.com.
