I am working with a highly collaborative, academic fund that is expanding rapidly in London. They are looking for entry level quantitative researchers coming from a PhD.
Key Responsibilities:
- Conduct research to identify and test new trading signals using statistical and machine learning techniques.
- Develop and refine predictive models to analyze financial markets and uncover opportunities.
- Collaborate with data scientists and engineers to preprocess and manage large-scale datasets.
- Design, implement, and backtest quantitative strategies across multiple asset classes.
- Monitor and improve the performance of existing models and strategies.
Preferred Qualifications:
- PhD in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, Engineering, or related disciplines.
- Strong programming proficiency in Python, R, or C++.
- Familiarity with statistical and mathematical modeling techniques.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus.
- Ability to tackle complex problems methodically and think critically about data and results.
- Interest in financial markets or prior exposure to financial data analysis is advantageous but not required.
- Effective communication skills and a collaborative approach to problem-solving.
If there is any interest, please apply directly or reach out to me on harry.moore(at)selbyjennings.com.