Aditya Iyer

Background

About Aditya Iyer

I’m a finance professional with 6+ years of experience at Morningstar, specializing in financial data research, IPO data validation, and building high-quality datasets used across global investment platforms. Over the years, I’ve developed a strong ability to interpret complex financial statements, standardize data under evolving global policies, and collaborate across Technology, Operations, Documentation, and Research teams to resolve issues and enhance data reliability.In my current role as Senior Data Research Analyst, I oversee IPO data workflows end-to-end. This includes monitoring new listings, validating document accuracy, executing SQL checks, and ensuring that foundational data reaches downstream teams correctly and on time. My work extends to resolving complex RTO (Reverse Takeover) scenarios, dual listings, cancellations, and other edge-case corporate actions that require analytical judgment and policy expertise. I’m also actively involved in cross-team initiatives, including being selected for a 3-month DBRSM Corp assignment under Morningstar’s resource-sharing program.Earlier, as a Data Research Analyst, I handled fundamental data mapping for financial services companies using Morningstar’s N/B/I/V templates, identifying revenue breakdowns, cost structures, and balance sheet–cash flow relationships. I also supported team-level allocations, shared performance dashboards, and mentored new analysts—helping them interpret data policies accurately and ramp up faster.My certifications and ongoing learning reflect my interest in combining fundamental research with analytics:• NISM Research Analyst (SEBI/NISM)• IFRS Certification – NSE/IMS• SQL (W3 Schools – ongoing)• Python (W3 Schools – ongoing)• Financial Modelling (Udemy – ongoing)• Generative AI & Prompt Engineering coursesI’m known for high-quality delivery, process rigor, and a strong work ethic—attributes recognized through multiple Spot Awards, 10+ Thank You cards, Star of the Quarter, and a promotion earned without applying internally. I’ve also contributed ideas for system enhancements to improve data accuracy and throughput during peak cycles.Going forward, I’m sharpening my skills in Python, SQL, and financial modelling to deepen my contribution to investment research, analytics, and data-driven decision making. I’m particularly interested in roles where data quality, financial modelling, and structured research intersect.