Data Research Analyst

Role : Data Research Analyst
Shift : AU/UK/US
Location : Vashi, Navi Mumbai
Work Mode : Hybrid(3 days WFO & 2 days WFH)
Job Description
Morningstar is one of the largest independent sources of Fund, Equity, Credit data and Research in the world, and our advocacy for investors interests is the foundation of our company. We provide independent analysis on individual securities, funds, markets, and portfolios. We also provide data on hundreds of thousands of investment offerings, including stocks, mutual funds, and alternative vehicles, along with real-time global market data on millions of equities, indexes, futures, options, commodities, and precious metals, in addition to foreign exchange and Treasury markets.
In this role as a Data Research Analyst, you will analyze, interpret and collect operational, document, performance, and portfolio data from various vendor sources. This role entails performing thorough research, generating valuable insights, and maintaining up-to-date data records. The ideal candidate possesses strong analytical skills, attention to detail, and proficiency in tools and techniques. Also adhere to the company goals, policies and procedures and work in a focused manner to achieve the overall objectives. You will be responsible for, with the help of leaders, ensuring and improving the performance, productivity and efficiency and the delivery of the operational performance KPIs. You will effectively manage your performance and development to support our continuous operational success.
Responsibilities:
1. Actively collect and manage investment data using Morningstar systems, ensuring timely, complete, and accurate data to meet business goals while maintaining productivity and adhering to quality standards.
2. Take ownership of data quality control to ensure consistency and high standards, meeting client and product requirements.
3. Manage relationships with asset management companies, insurance providers, and other data vendors to foster collaboration and data integrity.
4. Develop a comprehensive understanding of datasets, policies, and processes for regions under coverage to ensure informed decision-making.
5. Actively participate in team discussions, methodology reviews, and meetings to raise concerns, propose solutions, and contribute to decision-making.
6. Drive continuous process improvement through quality initiatives, using Lean Six Sigma tools, Continuous Improvement and automation.
7. Collaborate closely with quality assurance product, and technical teams to resolve client data issues effectively and efficiently.
8. Work with global teams on process management
9. Promote an automation mindset by identifying improvement opportunities and collaborating with leadership to drive process enhancements.
10. Ability to perform effectively under tight deadlines and manage pressure during peakperiods.
Requirements:
1.Bachelor's degree or higher in Economics, Finance, Business, Mathematics, or Statistics, and a solid understanding of fund investment data.
2. 1 - 2 years of experience in Data analysis, research or a related role, having knowledge of Capital markets and Secondary market is preferrable
3. Proficiency in MS Office tools (Excel, PowerPoint, etc.) and Experience with database management systems SQL; advanced users will be given preference.
4. Familiarity with data visualization tools (e.g., Tableau, Power BI) with a passion for learning, developing, and deploying solutions in the rapidly evolving AI/GenAI space.
5. Strong analytical and problem-solving skills, complemented by excellent written and verbal communication and reporting abilities.
6.Candidates should be flexible to work in shifts.
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.