Senior Data Research Analyst

Overview

Senior Research Analyst responsible for ensuring the integrity and accuracy of Morningstar's Fixed Income data and analytics, working with methodology analysts, product managers and engineering teams.

What you'll do

• Design, develop and maintain a comprehensive QA framework for Fixed Income data and analytics, including monitoring data processes, data completeness, accuracy and timeliness.
• Consistently improve existing model validation and QA processes, with an eye toward automation, efficiency and robustness.
• Leverage Data Science, AI and Large Language Models (LLMs) where possible to enhance analysis and generate actionable insights.
• Create and implement validation strategies for new data sets and analytical outputs, integrating these checks into production environments.
• Oversee the full lifecycle of vendor data, from ingestion through to analytics and insights production, to ensure outputs meet defined quality and accuracy standards.
• Validate the accuracy and integrity of Fixed Income calculations, metrics and models to ensure they align with established methodologies.
• Collaborate with Quantitative Analysts, Product Managers and Engineering teams to understand methodologies, resolve issues and drive continuous improvements.
• Handle client escalations by conducting thorough root cause analysis and facilitating timely communication and resolution with relevant stakeholders.
• Maintain a deep understanding of Morningstar's Fixed Income data models and infrastructure, ensuring end-to-end data quality from collection to reporting.

What you'll need

• Bachelor's or Master's degree in Finance, Economics, Data Science, Computer Science or a related quantitative field.
• Minimum 3 years of experience as a Research Analyst, Data Analyst or similar role within Fixed Income or Financial Services.
• Strong background in financial data analysis, particularly Fixed Income products and methodologies.
• Required: proficiency in SQL.
• Strong understanding of Fixed Income market instruments, calculations and metrics.
• Ability to interpret and ensure methodologies are correctly implemented in code and production environments.

Nice to have

• Proficiency in coding and reviewing production-level code in at least one statistical modeling language (Python or R) for validation and quality assurance.
• Experience developing QA frameworks for large datasets and complex analytics.
• Familiarity with data validation techniques, anomaly detection and root cause analysis.
• Knowledge of data science, AI and LLM tools for data insights and anomaly detection.
• Understanding of data lineage, data infrastructure and end-to-end data pipeline management.
• Hands-on experience with vendor data integration and quality monitoring.
• Familiarity with Morningstar data models and their end-to-end lifecycle.

Details

• Location: Mumbai, India.
• Work mode: hybrid, with four days in-office each week in most locations.
• Morningstar is an equal opportunity employer.