Data Analyst

S&P Global’s roots stretch back to 1860 with a vision for how Essential Intelligence could Accelerate Progress in the industrial revolution. Integrity, discovery and partnership are embedded into our identity.

New challenges to solve. New markets to navigate. New opportunities to capture. In a world that gets more complex by the hour, we will continue to provide the data, insights, technology, and innovation to help get our customers ahead.

S&P Global has been accelerating progress in the world since 1860, guiding our customers through uncertainty. Our values continue to underpin who we are and how we show up for our people, customers and communities.

1. High quality data (Financial / Non-Financial Data) collation, analysis, extraction and entering the data in work tools as per guideline specifications for assigned vertical
2. Understand the working of the dataset, be aware of the workflows and have strong working knowledge of work tools
3. Providing input and ideas for new collection methods and product enhancements related to the dataset
4. Deliver on predefined individual and team targets including delivering outcomes with quality and excellence.
5. Create tech expertise within department
6. Troubleshoots problems or issues and support team in enhancing the workflow/processes for department
7. Reviewing feedback involving transactions content to help correct errors and establish or refine procedures and processes to improve accuracy

1. Fresher - Post-Graduate / MBA in Finance as major Specialization with good academic track record (passing year 2024/2025)
2. Excellent communication skills, both written and oral
3. Knowledge of corporate finance / accountancy i.e., financial statements and annual reports
4. Well versed with secondary research sources
5. Willing to work in 24*5 environment on rotational shifts (including night shifts)
6. Certification or knowledge/experience in MS-office (Excel, Word, PowerPoint)
7. Strong quantitative, analytical, and interpretive skills
8. Ability to conduct efficient thematic online research