The quantitative Investment Portfolio Manager position is responsible for research and developing methodologies required for managing global multi-asset risk parity based portfolios. The researcher is required to innovative research across asset classes, as well as within the asset classes which are fixed income, equities, and commodities. The position is also responsible for generating publication-quality research, presentation of research results, and participating in the group research meetings and discussions. **ESSENTIAL FUNCTIONS** - Conduct alpha factor research for global equity strategies by generating creative investment ideas and rigorous quantitative analysts. - Apply statistical analysis and modeling techniques with finance intuition to datasets large and small, enhance existing models, and pursue new and previously unexplored research topics. - Perform advanced programming in Python/Pandas, R, and SQL, and highly customized data extraction from Factset, Bloomberg, Revere, and Thompson Reuters databases. Author research papers to showcase PanAgora's research depth. - Design and manage research agendas. Backtest and present research on equity investment factors. Communicate understanding of the market and how it impacts a client's portfolio. Advance research capabilities using modern machine learning techniques. **QUALIFICATIONS:** - Requires a Master's degree in Finance, Econometrics, Economics, Mathematics, or a directly related field plus three (3) years of experience conducting, summarizing, and presenting financial research analysis. - Must have three (3) years of experience in the following (experience may be gained concurrently): - Programming experience in Python and SQL - Experience running backtests and performing and summarizing quantitative equity research - Experience with advanced computer software programming and design, including pandas, scipy, or numpy - Experience with advanced mathematical modeling, including regression analysis, Linear Algebra, and Machine learning algorithms - Experience working with large data sets, financial statements, and other regulatory filings - Relevant theoretical and empirical factor research, forecasting methodologies, and portfolio construction techniques, including - Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), Fama-McBeth Analysis, Mean-Variance Portfolio - Optimizations, and Optimization Constraint Analysis - Must have two (2) years of experience in the following (experience may be gained concurrently): - Codifying investment strategies using Python, R, Perl, SQL, or C# - Adjusting models to manage portfolio-relevant systemic risk - Designing and implementing parametric and non-parametric models across different markets for long-term or short-term modeling - Must have one (1) year of experience in the following (experience may be gained concurrently): - Codifying investment strategies using machine-learning technologies for quantitative and textual data This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason. Base salary: $200,000 - $250,000 Disclaimer: The posted salary range represents the company's good faith estimate of the compensation for this position at the time of posting and the same is not a promise of a particular wage for any individual. Actual compensation may be dependent on a variety of factors including, but not limited to, the candidate's experience, education or skills, and other factors.