Morningstar's Quantitative Research Group creates independent investment research and data-driven analytics designed to help investors and Morningstar achieve better outcomes by making better decisions. We utilize statistical rigor and large data sets to inform the methodologies we develop. Our research encompasses hundreds of thousands of securities within a large breadth of asset classes including equities, fixed income, structured credit, and funds. Morningstar is one of the largest independent sources of fund, equity, and credit data and research in the world, and our advocacy for investors' interests is the foundation of our company.
As a Quantitative Analyst, you will be a highly visible representative of our quantitative research team. In this role you'll faithfully represent Morningstar's research, products, and data publicly to external clients and to internal stakeholders. You will work closely with the internal development teams to provide build out our automated text analysis solutions. In addition, you'll be responsible for authoring original investment research that helps investors. A successful candidate will have impeccable interpersonal and communications skills, a solid quantitative mindset, and a strong understanding of finance. This position is based in our Chicago office.
- Be a subject-matter expert on the topics of factor investing and portfolio construction.
- Assist in the management of relationships with internal stakeholders that influence and consume outputs from the methodologies developed by the quantitative research team.
- Generate original investment research with the goal of improving outcomes for our clients.
- • Assist in the production and writing of factor investing literature on a regular cadence.
- Faithfully represent the work of the quantitative research team to internal stakeholders and external clients.
- A bachelor's degree in quantitative or financial discipline (Masters or higher is desirable).
- Excellent written and oral communication skills.
- Experience with Morningstar's mutual fund, fixed income, and equity databases.
- Intermediate knowledge of statistical methods.
- Ability to stay organized and to quickly and efficiently handle multiple projects at the same time is crucial in this role.
- Ability to work collaboratively in a team environment, while also taking ownership of projects independently with minimal supervision.
- Familiarity in at least one statistical modeling language (Python or R).
- Familiarity with Agile software engineering practices.
- Familiarity with probabilistic sequence modelling techniques such as state-space models, particle filtering, decision processes, dynamic programming and reinforcement learning.
- Intellectual curiosity for the world of quantitative research.