Job Purpose and Responsibilities:
- Research and implement optimization routines for creation/redemption of ETFs.
- Build electronic market-making models (hedging algorithms, bid-offer models, price predictors, automated pricing models)
- Analyze performance of market-making operation and issue recommendations for model adjustments and new model development
- The candidate must be practically minded – he or she must understand how models generate value for the trading operation, what level of sophistication they should have in order to achieve their goals while remaining simple and easy to implement, and how model performance can be evaluated, both in testing and in production.
- The position requires both attention to details and the ability to see the “big picture” of the trading operation.
- Candidate must be technically strong and understand how to efficiently use the systems available for data analysis.
- Candidate must be very strong with statistics and data analysis and machine learning methods.
- New optimization algorithms and pricing algorithms, including short-term microstructure predictors.
- Automation of flow analysis and bid-offer spreads.
- Improvements to hedging and hedge execution algorithms
Skills and Qualifications:
- Extensive experience in statistics or machine learning and in a systematic trading field (execution algorithms/statistical arbitrage/electronic market making).
- Familiarity with corporate bond and interest rate products and market microstructure
- Attention to detail.
- Ability to work on a team and to work well under pressure.
- Strong written and verbal communication skills
- Strong programming skills in a scripting language (Python, R, Matlab) and in Java, C# or C++.
- Proficient in database applications (f.ex. KDB) and visualization tools.
- Ability to work with large data-sets.