Portfolio Optimization Leader
vor 3 Stunden
Job Description
MCP (Switzerland) GmbH is looking for a highly skilled Portfolio Optimization Leader to join our team. The successful candidate will be responsible for optimizing the company's portfolio through the development and maintenance of statistical arbitrage strategies.
Key Responsibilities
- Develop and maintain statistical arbitrage strategies for the company's portfolio.
- Analyze predictive mathematical models produced by researchers and develop algorithms to combine the models into a portfolio generating statistically significant returns.
- Construct new algorithmic trading strategies using predictions developed by researchers.
- Optimize the risk/reward ratio of the portfolio of own strategies.
- Apply filtering techniques to predictive signals in order to filter out random noise.
- Manage the day-to-day evolution of strategies in response to changes in the market environment.
- Stay on top of the latest quantitative research trends in both academia and industry.
- Evaluate and allocate capital to strategies, targeting optimal value-added to the company portfolio.
Requirements
- Master's or higher in Computer Science, Computer Engineering, Electronic Engineering, Statistics, Operations Research, or a closely related quantitative field.
- 5 years' experience as a Regional Research Director, Vice President, Research, Senior Quantitative Researcher, Quantitative Researcher, or in similar position(s), which must include:
- Experience working with Portfolio Managers and Researchers on alpha signal combination research and development.
- Experience using data API for trade execution to implement trading strategies individually developed, across major exchanges throughout the United States, Europe, and Asia.
- Mathematical maturity, and the application of data analysis, linear algebra, logic, probability, statistics, and optimization techniques.
- Experience applying advanced statistical modeling techniques, including machine learning, regression, and multivariate statistics.
- Programming experience in C++, Python, Matlab, or R programming languages; and SQL.
- A good understanding of equity, futures, and currency markets.
- Experience with Linux operating system.
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