Bloomberg - Equity Factor Modeler

Employment Type: Permanent
Location: New York - New York, United States of America
Salary: Competitive
Name: Bloomberg
Posted: 14-03-2012
Code: 27180
Languages:
English
Required Languages: 0

Bloomberg is the world's most trusted source of information for businesses and professionals. Bloomberg combines innovative technology with unmatched analytic, data, news, display and distribution capabilities, to deliver critical information via the BLOOMBERG PROFESSIONAL® service and multimedia platforms.

The Role

The ALPHA Quantitative Researcher role is responsible for research and development of ALPHA: Bloomberg's Investment Portfolio Analytics & Risk product. General responsibilities include: conducting value-added research in the areas of risk model development, portfolio management, portfolio optimization, risk hedging/mitigation, performance attribution etc;

This role plays a vital part in building out a cutting-edge, world-class portfolio analytics and risk platform on Bloomberg. The system includes portfolio optimization, factor modeling, asset allocation, trade execution, index replication, hedging tools, etc.

This multi-asset class platform will cover equity, fixed income, currency, commodity, and non-traditional asset classes. The models you build will be relied upon by risk and portfolio managers for stress testing, scenario analysis, tracking error calculations, portfolio construction, attribution, trading list analysis as well as VaR estimation.

You will generate innovative ideas, develop state-of-the-art equity factor models and perform independent research that helps clients improve the investment management process; supervise model implementation in the software product, publish white papers and educate Bloomberg clients.

Qualifications:

The ideal candidate is familiar with finance theory, asset pricing, factor modeling, and optimization theory, both at the theoretical level as well as for practical purpose. Ability to manipulate large datasets and perform statistical analysis is essential. Knowledge of advanced statistics and econometrics is required.

Experience with SAS, R, S+ or MATLAB is a strong plus. Good working knowledge of factor model techniques is required. A PhD in natural sciences, finance, economics or a related field and a minimum of 5 yrs of industry or relevant academic experience at a top institution is required.