What are the responsibilities and job description for the Artificial Intelligence Researcher position at Aurum Search Limited?
We are seeking a highly skilled Artificial Intelligence (AI) Researcher to join a quantitative research and investment team at a leading multi-strategy hedge fund. In this role, you will leverage machine learning, deep learning, and advanced AI techniques to enhance alpha generation, portfolio optimization, and risk management strategies. You will collaborate with portfolio managers, quantitative researchers, and data scientists to develop cutting-edge AI-driven models that contribute directly to the firm’s investment decision-making process.
Key Responsibilities
- Research and develop AI-driven models to extract tradable signals from structured and unstructured financial data.
- Apply machine learning, deep learning, NLP, and reinforcement learning to enhance trading strategies.
- Work closely with quantitative researchers and portfolio managers to integrate AI models into systematic and discretionary trading strategies.
- Optimize existing models for predictability, robustness, and computational efficiency.
- Leverage alternative data sources to uncover new investment opportunities.
- Design and implement backtesting frameworks to evaluate AI-based strategies.
- Stay at the forefront of AI advancements and assess their applicability to financial markets.
Qualifications & Experience
- Ph.D. or Master’s degree in Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
- Strong programming skills in Python (NumPy, Pandas, TensorFlow, PyTorch, Scikit-learn) or C .
- Deep understanding of machine learning techniques, including supervised/unsupervised learning, deep learning, Bayesian methods, reinforcement learning, and NLP.
- Experience in financial markets, quantitative research, or systematic trading is highly desirable but not mandatory.
- Proficiency in handling large-scale financial and alternative datasets.
- Experience with cloud computing, distributed computing, or high-performance computing is a plus.
- Strong analytical mindset with the ability to interpret and communicate complex AI models to non-technical stakeholders.
