About Us: Morningstar DBRS is a leading provider of independent rating services and opinions for corporate and sovereign entities, financial institutions, and structured finance instruments globally. Currently with 700 employees in eight offices globally. Formed through the July 2019 acquisition of DBRS by Morningstar, Inc., the ratings business is the fourth-largest provider of credit ratings in the world.
Morningstar DBRS is committed to empowering investor success, serving the market through leading-edge technology and raising the bar for the industry. Morningstar DBRS is a market leader in Canada, the U.S. and Europe in multiple asset classes.
Morningstar DBRS rates more than 4,000 issuers and 60,000 securities worldwide and is driven to bringing more clarity, diversity of opinion, and responsiveness to the ratings process. Morningstar DBRS approach and size provide the agility to respond to customers’ needs, while being large enough to provide the necessary expertise and resources.
Visit: Morningstar DBRS | Global Credit Rating Agency & Research to learn more.
About the Role: Morningstar DBRS Structured Finance Analytics team is looking for candidate with good problem solving, analytical & technical mindset. As an Analyst, you will work with team to automate data analysis processes to include document downloads, data storage, build and run data analytics to aid rating, research, and surveillance process, develop and enhance data analysis and workflow optimization tools; assist with special projects/initiatives, as needed. Proficiency in Python, Tableau, SQL and VBA will be needed. This role will provide unique opportunities for mastering the key aspects of our business including in-depth collateral and deal analysis. This position is based in our Navi Mumbai office.
Responsibilities:
- Work with Associate Quant Analyst to deliver projects and services.
- Assist the team with transforming, improving and integrating data, depending on the business requirements.
- Combining the data result sets across multiple sources
- Understand core concepts around data storage and access specifically in structured data systems such as databases (SQL, Athena, AWS S3)
- Participate actively in the design and build phases, to aim at producing high quality deliverables.
- Have a mindset to bring about process efficiencies and ideate automations
- Collect, organize, and study data from internal and external sources for use in criteria development, ratings, and research reports.
- Take ownership of the tasks with focus on quality and accuracy of the deliverables
- Demonstrate strong learning curve
- Highly organized and efficient, with ability to multi-task and meet tight deadlines
- Ensure compliance with regulatory and company policies and procedures
Requirements:
- Bachelor’s degree in Engineering or other quantitative discipline, Finance or Management Studies.
- Masters, Postgraduate in Data Analytics/Science program enrollment are a plus
- 1-2 years of experience working with financial products using Python.
- Proficiency in Python / Anaconda, Data science stack (Jupyter, Pandas, NumPy), Tableau, Microsoft Excel, Visual Basic for Applications (VBA) and MSSQL.
- Proficiency in object-oriented programming is a plus.
- Strong attention to detail and accuracy
- Highly motivated, self-starter who is keen to learn, has a positive attitude and a strong work ethic
- Ability to manage multiple tasks at the same time and deliver results in a timely manner
- Good inter-personal skills and ability to participate/ contribute as a team player
Morningstar DBRS is an equal opportunity employer.
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office 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.
Skills Required
- Bachelor's degree in Engineering, another quantitative discipline, Finance, or Management Studies
- 1-2 years of experience working with financial products using Python
- Proficiency in Python and Anaconda
- Proficiency with Jupyter, Pandas, and NumPy
- Proficiency in Tableau
- Proficiency in Microsoft Excel and Visual Basic for Applications (VBA)
- Proficiency in MSSQL
- Strong attention to detail and accuracy
- Ability to manage multiple tasks and deliver results on time
- Good interpersonal and teamwork skills
- Master's or postgraduate enrollment in Data Analytics or Data Science
- Object-oriented programming experience
What the Team is Saying
Morningstar Compensation & Benefits Highlights
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Retirement Support — Employer 401(k) matching and access to Morningstar retirement‑planning tools are prominent features of the package. These elements create a strong foundation for long‑term savings.
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Leave & Time Off Breadth — Flexible time off, paid holidays, sick and personal days, and a paid sabbatical every four years provide generous time away from work. Sabbaticals are specifically highlighted as a standout perk.
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Parental & Family Support — A global minimum of 16 weeks for primary caregivers, up to eight weeks for secondary caregivers, and at least six weeks of paid caregiving leave offer robust family support. Some materials also note adoption assistance and related resources.
Morningstar Insights
What We Do
We are a global investment research and financial data company with 40-plus offices across North America, Europe, Australia, and Asia. Our products and services are used daily by individual investors, financial advisors, asset managers, retirement plan providers, and institutional investors. We provide data, research, and analysis across managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. The financial system can have real barriers—hidden information, friction that can slow decisions, and forces that can limit transparency and access. We work to remove them, bringing independent research, connected data, and investor-first tools to a system that needs more clarity. The people doing this work span research, technology, design, product, sales, and functional areas. We build many of our products in-house, so the work can connect directly to the tools investors use to make real financial decisions.
Why Work With Us
Morningstar’s missing is to empower investor success. We can only do that if our people feel empowered. That means finding people who think independently, bring a wide range of backgrounds with analytical rigor and genuine intellectual curiosity to the work.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.
