Equity markets move fast and existing alphas decay due to their short life-span. To capture ever-shifting market dynamics, a successful fund needs to keep pushing the boundary and generate new alphas from various data sources. This position sits within the research team and will focus on researching and testing new ideas to generate alphas and to research and design statistical strategies and optimize of portfolios.
Key Points:
- Alpha generation
- Back-testing
- Productionizing Strategies
- Statistical Arbitrage
- Equity Price Prediction
- Strong focus on statistical machine learning
Preferred Background:
- PhD in Statistical Machine Learning
- Undergraduate degree with a 3.8 GPA or higher
- Publications in top tier Journals
- At least 2 years of real world experience (post PhD) with a research focus on Statistical Machine Learning applied to the real world.
Core Competencies:
- Probabilistic models, approximate posterior inference; scalable algorithms for learning from networks, genetic variation and recommendation data sets
- Kernel Methods for Statistical Learning
If you would like to be considered for the position of Quantitative Researcher, or wish to discuss the role further then please leave your details below. Your resume will be held in confidence until you connect with a member of our team
