Responsibilities:
- Develop and implement AI and machine learning models to analyze financial data and generate predictive insights that support trading strategies.
- Perform in-depth data analysis, utilizing large datasets to identify trends, patterns, and anomalies that can inform investment decisions.
- Conduct research to develop and refine models, leveraging the latest advancements in AI/ML methodologies.
- Design and test models and algorithms to support trading strategies, ensuring they are robust, efficient, and scalable.
- Work closely with Portfolio Managers and Researchers to integrate AI/ML models into the firm's trading systems and strategies.
- Document research findings, model development processes, and performance metrics. Communicate results to both technical and non-technical stakeholders.
Qualifications:
- PhD ideally in AI/ML, but could be in STEM with a focus in AI/ML
- Prior experience in finance is a plus
- Proficiency in programming languages commonly used in AI/ML and quantitative finance, such as Python, R, or MATLAB.
- Strong knowledge of AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and experience applying these techniques to real-world data.
- Excellent quantitative skills with the ability to develop and interpret complex models and algorithms.
- Experience with data manipulation, cleansing, and preprocessing techniques. Familiarity with big data technologies is a plus.
- Strong analytical and problem-solving skills, with a creative approach to developing innovative solutions.
