Senior Data Research Analyst

Morningstar; Mumbai City; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Morningstar India is seeking a Senior Research Analyst to strengthen QA for Fixed Income data and analytics. You will design validation checks, review production code, ensure methodologies translate into reliable system processes, and support data quality across the data lifecycle.

Collaborate with methodology, product, and engineering teams, manage client escalations, and drive improvements using data science tools and AI/LLMs where applicable.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field (Finance/Economics/Data Science/CS)
• Minimum 3 years of experience as a Research Analyst/Data Analyst in Fixed Income or Financial Services
• Strong background in financial data analysis, particularly Fixed Income products and methodologies

Responsibilities

• Design, develop, and maintain a QA framework for Fixed Income data and analytics.
• Improve model validation and QA processes with automation, efficiency, and robustness.
• Create validation strategies for new data sets and outputs in production environments.
• Oversee vendor data lifecycle from ingestion to analytics to ensure quality.
• Validate Fixed Income calculations, metrics, and models against methodologies.
• Handle client escalations with thorough root cause analysis and timely communications.
• Maintain understanding of Morningstar Fixed Income data models and end-to-end data quality.

Skills

SQL

Python

R

Data validation techniques

Root cause analysis

QA frameworks development

Data quality Monitoring

Fixed Income knowledge

LLMs for data insights

Education

Bachelor’s or Master’s degree in Finance, Economics, Data Science, Computer Science

Tools

Python

R

Job description

The Role:

As a Senior Research Analyst, you will play a pivotal role in ensuring the integrity and accuracy of our Fixed Income data and analytics. Working closely with Fixed Income Methodology Analysts, Product Managers, and Engineering teams, you will design and implement robust validation checks that uphold the quality of our production environments. Your strong analytical background will enable you to review production code critically, ensuring methodologies are correctly translated into system processes and that models perform effectively.

You will be responsible for developing quality assurance frameworks, monitoring data health, and validating new data content and analytics to maintain high standards throughout the entire data lifecycle. Additionally, you will manage client escalations by performing detailed root cause analysis and collaborating with internal teams to resolve issues efficiently.

This role requires a proactive individual with a strong understanding of Fixed Income markets, data science tools, and end-to-end data processes to help drive data accuracy, reliability, and insightful analysis..

Responsibilities:

• 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 upon 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 seamlessly into production environments.
• Oversee the full lifecycle of vendor data—from ingestion through to analytics and insights production to ensure all 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 closely 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.

Requirements:

Education & Experience:

• 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.

Technical Skills:

• Required: Proficiency in SQL
• Preferred: Proficiency in coding and reviewing production-level code in at least one statistical modeling language (Python or R) for validation and quality assurance purposes.
• 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.
• Strong understanding of Fixed Income market instruments, calculations, and metrics.
• Ability to interpret and ensure methodologies are correctly implemented in code and production environments.
• Familiarity with Morningstar data models and their end-to-end lifecycle is a plus.

Morningstar 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.

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