Quantitative Risk Analyst recruitment
Quantitative Risk Analyst
Responsibilities
Quantitative Risk Analysts will be responsible for conducting research and analysis in the evaluation of securities utilizing fundamental, technical, statistical, and/or quantitative methods to provide support for Portfolio Managers on the fund platform. In addition, duties may include monitoring market, industry, product, and pricing trends by providing technical and product support. Responsibilities may also include:
- Research the risk and portfolio construction questions of the fundamental analysts and portfolio managers
- Construct and apply multi-factor risk models to improve portfolio construction
- Communicate reporting output from risk models to fundamental analysts and portfolio managers
- Work closely with traders to interpret valuations and develop next generation models and analytics
- Provide high level technical and investment analytic support to the trading desk
- Assist users of QR tools, products and services to ensure that applications meet user requirements, and that users understand all implications
- Conduct research in equity transaction cost efficiency and portfolio optimization
Qualifications
The successful candidate will be a self-starter who has demonstrated the ability to function in a fast-paced, dynamic, and demanding environment. This person will be intellectually curious, intuitive, rigorous, trustworthy, and have the ability to work in a team oriented setting. We are looking for candidates with proven abilities to conduct research under general guidance, but mostly independently.
- Previous exposure to a quantitative role within a trading environment is a plus
- Knowledge of optimization theory and working with optimization tools
- Good coding skills, familiarity with Python, C++ , R or other scripting languages is a plus
- Strong mathematical and/or statistical modeling and strategy implementation skills
- Knowledge of Matrix algebra and regression analysis
- Comfortable with analysis of large datasets
- Firm foundation in statistics and well-developed mathematical, econometric, and financial knowledge
- Bachelors in statistics, mathematics, computer science, physics, or financial engineering
- Masters or PhD in statistics, computer science, or financial engineering
- Experience with multifactor models