PhD - Quantitative Researcher - Risk Modeling and Research - Financial Data/Software

  • Competitive market salary and benefits
  • Riga, Latvia
  • Permanent, Full time
  • FACTSET
  • 19 Feb 18 2018-02-19

The Quantitative Researcher will work in the fast expanding international FactSet Risk Research, Strategy and Modeling group, participating in research and development of the state of the art mathematical models of investment risk. The position requires a PhD in mathematics, physics, and/or statistics along with exceptional technical skills and the ability to communicate complex concepts clearly and effectively to colleagues and clients of varying levels of sophistication. The Quantitative Researcher will work in FactSet Riga office (Latvia).

We offer unique career opportunity to an innovative and passionate individual:

  • Application of your advanced knowledge and skills in mathematics, probability theory and statistics
  • Work in a collaborative and research oriented team environment
  • Opportunity to learn from industry renowned experts, to acquire detailed knowledge of financial mathematics, asset pricing theory and risk modeling techniques
  • Competitive compensation package, health insurance, reimbursement of relocation expenses
  • Future career growth, future opportunity to work in other FactSet locations around the world

In this role the candidate will:

  • Participate in every stage of FactSet’s modeling/research effort in quantitative risk as part of international team of world-class specialists in mathematical finance
  • Learn about financial markets, advanced risk models and portfolio management techniques
  • Be responsible for creating advanced mathematical models for financial markets volatility forecasts, complex market factor decomposition models, multidimensional market correlation structure models, portfolio optimization tools and future market scenario analysis methodologies

Job Requirements

  • PhD in mathematics, physics, statistics, or related field
  • Exceptional analytical proficiency and problem solving skills
  • Ability to work independently on every stage of design of advanced mathematical models is critical to this position
  • Strong knowledge of linear algebra, probability theory, statistics and numerical methods
  • Experience working with large data sets, statistical data analysis, building multivariate regressions models
  • Knowledge of time series analysis techniques and models is highly desirable
  • Ability to communicate complex concepts clearly and effectively
  • Knowledge of programming (Python, C++), knowledge of object oriented paradigm is preferable
  • Knowledge of quantitative finance is not required