About the role
Join our dynamic trading team at Freedx as a Junior Python Trading Research Analyst! We are seeking an analytical and inquisitive individual who thrives on working with Python and analyzing market data to derive actionable insights. This position offers you the opportunity to gain practical experience in real-world trading scenarios and contribute to our market-making research.
About Freedx
Freedx is a pioneering cryptocurrency exchange committed to providing a seamless, secure, and innovative trading experience. Our team comprises industry veterans from the cryptocurrency, finance, and technology sectors, driven by a common goal of transforming digital finance. We aim to be the most trusted exchange, offering users the confidence and freedom to manage their digital assets efficiently. Our core principles of security, transparency, and scalability guide our continuous innovation to meet the evolving demands of traders, equipping them with advanced tools and services to help achieve their financial aspirations.
Become a part of our mission to redefine digital asset trading and bring true freedom and reliability to the crypto landscape.
Your Responsibilities
1. Market Data Analysis
- Analyze order book data, including spreads, depth, and liquidity layers.
- Investigate market microstructure, focusing on order flow and volatility patterns.
- Study market behavior across different volatility conditions.
- Conduct research on basis, funding, contango/backwardation, and cross-exchange discrepancies.
2. Statistical Modeling
- Create fundamental statistical models to identify regime shifts and volatility clusters.
- Examine correlations between features and realized PnL.
- Establish simple metrics to assess market quality and liquidity.
3. Machine Learning Research
- Implement machine learning techniques on order book features and short-term price predictions.
- Assess model stability, latency impacts, and risks of overfitting.
4. Algorithm Analysis
- Test traders’ hypotheses and concepts.
- Organize findings into models that can enhance production strategies.
5. Backtesting & Simulation
- Create lightweight environments for market making and directional strategies.
- Evaluate strategy variations under diverse market assumptions.
- Model hedging efficiency across various exchanges and instruments.
- Conduct scenario-based stress tests, including volatility spikes and liquidity shortages.
