Portfolio Manager & Senior Quantitative Analyst (8201BR) New York, New York

A senior quantitative equity analyst with portfolio management responsibilities will play a role in the development and implementation of quantitatively managed products as part of Cornerstone Capital Management (CCM)'s Global Quantitative Portfolio Management Team. Job requirements include: Improve CCM's stock selection models by identifying and developing new sources of alpha through factor modeling and/or new sources of data. Conduct portfolio construction research using Axioma’s optimization software to improve the implementation of CCM’s quantitative portfolios. Market strategies to new and existing clients Participate in trade preparation and rebalancing of long only and hedge fund portfolios. Enhance CCM's suite of factor diagnostic tools by applying rigorous statistical methods using SPlus software. Provide sales team with insightful performance reviews, commentaries and ad-hoc requests for analysis. Develop and maintain existing code library to support research and investment process

10+ years of quantitative equity research with 5+ years experience in buy side quantitative equity portfolio management. Experience building and modifying quantitative models with a 6-12 month investment horizon Strong communication skills with client facing experience Undergraduate degree in engineering, economics, finance, computer science, statistics or related major MBA, Masters, or CFA qualification Expertise in factor research & development, factor backtesting, optimized backtesting, and multifactor modeling Computer science and statistics knowledge is required to write and develop new factors, diagnostics, tools and reports Experience developing object oriented computer programs Experience working with UNIX based computer systems Strong Excel skills

Experience performing international quantitative research and portfolio management Axioma (preferred) or Barra Optimization and Backtesting knowledge Experience with performance and factor attribution Programming using a statistical package such as: Splus or R (preferred), Matlab, or SAS Programming using a database containing financial data such as: Factset Vision (preferred), MarketQA, Capital IQ
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