Senior Quantitative Researcher – Internal Equity Management

Richmond, Virginia (US)
Commensurate with experience
May 24, 2019
Jun 17, 2019
Position #445
Job Function
Industry Sector
Employment Type
Full Time

Posting Period:  May 23rd - June 17, 2019

The Virginia Retirement System’s (VRS) Internal Equity Management (IEM) team in the Investments Department is seeking an experienced professional to assist with the management and oversight of the internally managed equity investments.  Please visit VRS' website ( for additional information on the agency and fund.    


The IEM team currently manages over $14 billion of equity assets in a combination of quantitative active and passive funds and is currently developing several new strategies.  Internal funds are managed using a team approach in which each member of the group is responsible for generating new investment ideas, critiquing and refining the ideas of others, and implementing those ideas in tradable investment strategies.  The candidate should have a demonstrable track record of conducting long-term independent research projects including leading individual contributors, communicating complex ideas to multiple audiences and implementing successful ideas into the investment process.

The new team member will:

  • Develop proprietary stock selection and risk models
  • Design and construct large datasets to test investment ideas
  • Participate in the portfolio management and implementation process
  • Present research to the staff, Investment Advisory Committee, and Board 


The VRS expects the candidate to have:

  • Master’s-level background in financial market theory, economic theory, statistics, and econometrics or demonstrated equivalent.
  • A minimum of eight years of investment-related professional work experience.
  • Understanding of accounting and financial statement analysis and familiarity with asset pricing, macroeconomic and trading research.
  • A CFA charter is desirable. 
  • Strong programming skills to manage the data required for strategy research and implementation.  This includes SQL database programming and mastery of a high-level programming language such as R, MATLAB or Python.
  • Experience using financial databases such as Compustat, WorldScope, IBES and Bloomberg.
  • The ability to manage a collaborative research agenda.

Additional valuable skills would include:

  • Familiarity with optimization engines.
  • Familiarity with time series models and machine learning techniques.
  • Operational portfolio management including index construction and corporate action processing.