We are looking for a Quantitative Analyst who will be responsible for developing and implementing AI-driven models and algorithms to enhance our investment strategies. The ideal candidate will have a strong background in quantitative analysis, machine learning, and programming, with a focus on Python.
Key Responsibilities:
- Research, develop, and implement quantitative models and algorithms leveraging AI techniques such as machine learning, deep learning, and natural language processing.
- Analyze large datasets to identify patterns, trends, and insights that can be used to enhance investment strategies.
- Collaborate with portfolio managers and other stakeholders to understand their investment objectives and develop tailored solutions.
- Conduct backtesting and performance analysis to evaluate the effectiveness of quantitative models and strategies.
- Stay abreast of the latest developments in AI, machine learning, and quantitative finance, and incorporate relevant advancements into our processes and methodologies.
- Work closely with the technology team to implement scalable and efficient solutions for model deployment and productionization.
Qualifications:
- Master's or Ph.D. in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, or Physics.
- Strong quantitative skills with a deep understanding of probability theory, statistics, and optimization.
- Proficiency in Python programming and experience with relevant libraries and frameworks such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
- Solid understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, reinforcement learning, and deep learning is highly desirable.
- Experience working with financial data and applying quantitative techniques to investment analysis.
- Excellent communication and collaboration skills, with the ability to explain complex concepts to non-technical stakeholders.
