Risk & Quantitative Analysis Multi Asset Class Ph.D. Intern

BlackRock offers a range of investment products—equity, fixed income, liquidity, and alternative investment—each of which is managed by a dedicated investment team of portfolio managers, research analysts, and traders. Focused portfolio management and proprietary research are the cornerstones of our investment philosophy, and portfolio construction is based on each team’s market outlook. Our portfolio teams manage assets for institutional and individual investors alike. Accordingly, all of our clients benefit from our portfolio management expertise and risk management analytics.

The Opportunity:

As a result of our continued growth, we are looking for a statistics or finance-related Ph.D. student (3rd year or 4th year) who wishes to apply his/her analytical and creative skills to a part-time internship during the academic year of 2008/2009. This intern will join the Risk and Quantitative Analysis - Multi-Asset Class team in New York City.

The Team:

The Risk and Quantitative Analysis - Multi-Asset Class team is a “SWAT” team of problem solvers consisted primarily of PhDs from top schools to address quantitative problems for a highly visible product group of BlackRock, which includes the flagship Global Allocation team, BlackRock Alternative Advisors, Multi-Asset Portfolio Strategies, as well as a variety of structured products and other alternative investments.

The Requirements:

A qualified candidate will have completed his/her Ph.D. Qualifying exam in finance or statistics. PhD students in Finance are expected to have completed a quantitative sequence equivalent to the first-year PhD courses in Statistics. You should be a self-starter with the proven ability to produce documented research or complete projects independently. Finally, to be successful at BlackRock, you will exhibit excellent interpersonal as well as written and verbal communication skills.

The Responsibilities:

As a Quantitative Intern, you will be responsible for solving some of the most complex, leading-edge quantitative problems ranging from tail risk analysis to advanced hedging techniques to new product ideas. The quality of your work is expected to be near publication quality, but with "real world" contents.