About the Role
In this role, you will participate in the analysis of new feature/content requests and help multifunctional development teams to understand WHAT needs to be done to meet internal and external user's needs through Morningstar's next-generation data platform. You will also participate in the design/implementation of models to help with analysis of large datasets. You will be responsible for helping SOLVE the problem through use of up-to-date methods including AI/ML implementation. Finally, you will write documentation to build a deep knowledge base for global client support teams to investigate issues and answer clients' questions. The ideal candidate will have a passion for data and technology, excellent communication capability, and the ability to develop a strong understanding of Morningstar data and methodologies.
This position is based in our Toronto office. We follow a hybrid policy of 3 days onsite and 2 days remote work.
Job Responsibilities:
- Design and implement models that can analyze large datasets
- Develop and implement statistical, Machine Learning and AI solutions to make systems and processes more efficient
- Execution of both statistical and predictive analysis
- Communicate with internal and external clients, client success teams to understand and clarify business requirement
- Convert business requirements into actionable solutions through detailed analysis such as calculation prototyping, usage analysis, and data mapping/mining/locating in various data sources
- Ability to understand and surface repetitive methodologies to drive uniformity in data (consilience)
- Gathering, cleaning, and processing raw data/data sets
- Analyzing and interpreting unstructured data sets
- Comprehends functional requests from direction of product team and help determine solution validity and/or alternate options
- Leads team discussions to determine MVP for new projects
- Stay abreast of industry trends and advancement in data science, Machine Learning, and AI continuously improving our methodologies and technologies
Qualifications:
- 3+ years of advanced business analysis or data science
- 1-2+ years of experience with Morningstar software and or Data (bonus if in calculated or analytical data sets)
- Self-motivated, excellent work ethic, strong interpersonal and communication skills, ability to work in a team environment
- Excellent problem-solving skills
- Ability to learn quickly and work independently
- Advanced knowledge in data business and methodology of Equity, Fund, and Fixed Income
- Advanced knowledge of SQL, Python - a must have
- Advanced knowledge of Jupyter notebook, Amazon web service
- Intermediate knowledge of Plotly and PowerBI
100_MstarResCanad Morningstar Research, Inc. (Canada) Legal Entity
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
Top Skills
What We Do
At Morningstar, we believe in building great products in-house in a highly collaborative, agile environment where we focus on technical excellence, the user experience, and continuous improvement. Our technologists represent a range of skills and experience levels, but they all view their work as a craft and push technology’s boundaries.
Why Work With Us
Imagining big things is in our blood -- it's transformed us from a company with just a few employees in 1984 to a leading independent investment research company with a worldwide presence today. As of April 2020, we acquired Sustainalytics to drive long-term meaningful outcomes for investors in the ESG space. Join us on this exciting journey!
Gallery
Morningstar Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.