Quantitative Research Analyst
The Group: Morningstar Investment Management’s Research Group creates independent investment research and data-driven analytics designed to manage and advise on individual investor portfolios. The investment management group currently manages and advises on over $220 billion in assets globally. Our research encompasses asset allocation, portfolio construction, and lifecycle investing using various statistical and optimization frameworks for, primarily, on-line applications.
The Role: As a Quantitative Research Analyst, you will be a vital member of our research team. You will aid in the development of quantitative investment methodologies with the goal of helping to operationalize them. You will assist in the full product development cycle; from R&D to implementation to the maintenance of prototype and (to a lesser extent) production code bases that deliver our investment advice. A successful candidate will have strong interpersonal and communications skills, a solid quantitative background, and a strong interest in and understanding of finance and/or economics. This position is based in our Chicago office.
Responsibilities:
- Faithfully represent the work of the quantitative research team to internal stakeholders and external clients
- Help generate original investment research with the goal of improving outcomes for investors
- Assist in the development of production applications that incorporate numerical techniques such as linear algebra, machine learning, statistics, and optimization.
- Become a subject-matter expert in fund statistics, portfolio construction, optimization, etc., as well as Morningstar’s proprietary methodology and data points.
Requirements:
- Intellectual curiosity for the world of quantitative investment research
- A bachelor’s degree in quantitative or financial discipline (Masters or higher is desirable)
- Minimum 5 years of relevant experience, or 3 years with MSc+
- Intermediate to expert level with MATLAB and at least rudimentary familiarity with Python.
- Intermediate knowledge of statistical methods and optimization
- Working knowledge of portfolio construction and performance measurement
- Proficiency with SQL is desirable but not necessary
- Excellent written and oral communication skills
- Ability to meet strict deadlines and juggle various tasks while maintaining attention to detail and accuracy in running and proofing analysis
- Ability to work collaboratively in a team environment, while also taking ownership of projects independently and with minimal supervision