We are looking for Quantitative Researchers to join our Global Equities Team. You will have a chance to build alphas, and conduct research working with datasets covering over 10 different equity markets - US, Japan, China, and others. You will be a part of a dynamic, collaborative research organization. We expect you can work independently, and present the result in a structured, comprehensive manner.
Location
Yerevan, Armenia (Hybrid mode with 3 days in-office requirement)
Key Responsibilities
- Building statistical and predictive models
- Apply rigorous modeling techniques to explore variety of novel datasets
- Build new and improve existing signals (long-term)
- Managing all aspects of the research process, including methodology selection, data collection/normalization and analysis, prototyping, backtesting, and performance monitoring
Basic Requirements
- Physics, Mathematics, Computer Science, Engineering or other technical degree
- Practical Knowledge of Python and Python libraries (NumPy, Pandas, etc)
- OOP basics
- ML Basics
- Math skills: statistics, linear algebra, optimization etc
- Detail-oriented approach
- Cross-team communication
Nice to have Requirements
- Practical knowledge with Java
- Phd in Physics, Mathematics, Computer Science, Engineering or other similar area
- Experience participating in international STEM Olympiads
What you’ll get
- Freedom to choose your research direction
- Build Strategies while becoming the best at what you do
- Professional guidance from the team
- Challenges and professional growth
What makes you a match
- You LOVE solving technical and math problems!
- You love to code and play with data
- You know how to get people to listen to your ideas
- You are capable of understanding and improving legacy codebase
- You are willing to explore new articles and implement suitable ideas
- Difficult problems make you excited
- You are not afraid of unknown and love to learn
- You have A LOT of passion and drive
Benefits
- Health insurance
- Flexible sick time policy
- Office Lunches
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