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.
