Research Fellow (Mathematics)
Job Description
The candidate will work closely with the research team to develop advanced methods in Reinforcement Learning under Uncertainties for Reliable Autonomous Decision-Making in Finance.
Primary responsibilities will include:
- Data Management: Utilize proficiency in SQL, NoSQL, and vector databases to collect, clean, and manage data for research projects.
- Research Assistance: Collaborate on research initiatives focused on decision-making in finance, applying quantitative finance and econometric methodologies to analyze data and develop models.
- Machine Learning: Apply expertise in reinforcement learning and traditional machine learning algorithms to develop predictive models and optimal strategies.
- Programming: Utilize skills in Python, TypeScript, and JavaScript, along with frameworks like PyTorch, to implement and test quantitative models.
- Financial Expertise: Apply knowledge of finance, especially in risk management and equity markets, to contribute valuable insights to research projects.
- Communicate research outcomes through peer-reviewed publications and other scholarly dissemination channels.
Qualifications / Discipline:
PhD in Mathematics/Statistics/CS.
Skills:
- Proficiency in reinforcement learning, quantitative finance, risk management, and machine learning.
- Strong programming skill in Python, TypeScript, and JavaScript, along with frameworks like PyTorch.
- Excellent problem-solving abilities and attention to detail. Strong written and verbal communication skills.
Experience:
Strong preference for candidates with peer-reviewed publications, patents, conference presentations, research grants, or industry R&D contributions.
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