Data Science Contractor - AMM Yield Optimisation Model
About the Role
You will research AMM protocols and current dynamic fee approaches, investigate academic and industry literature on loss versus rebalancing and related concepts, and develop a dynamic fee model that accounts for volatility, gas prices, trading volume, and other factors. You will configure and validate the model using historical protocol data, document your methods and results, present recommendations to stakeholders, and work with developers to integrate the model into an AMM.
Requirements
- Bachelor's or Master's degree in Data Science Computer Science Statistics or a related field
- Proven experience building and implementing statistical models preferably in crypto or finance
- Strong understanding of AMM protocols including fee structures and yield optimization strategies
- Proficiency in Python or R and experience with pandas NumPy and TensorFlow
- Excellent research skills to synthesize complex concepts related to dynamic pool fees
- Strong communication and presentation skills
- Self-motivated and able to work independently while collaborating with cross-functional teams
Responsibilities
- Research AMM protocols such as Uniswap and Sushiswap
- Investigate leading research in dynamic pool fees and related concepts
- Develop a comprehensive dynamic fee model considering volatility gas prices and trading volume
- Configure model parameters and validate models using historical protocol data
- Document findings and present recommendations to stakeholders
- Collaborate with the development team to integrate the dynamic fee model into the AMM