Senior Data Research Analyst

Posted 20 Minutes Ago
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Mumbai, Maharashtra, IND
Hybrid
Senior level
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
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The Role
Develop and maintain QA frameworks for Fixed Income data and analytics. Validate data, models, calculations, methodologies, and production code across the vendor data lifecycle. Monitor data quality, detect anomalies, perform root cause analysis, and resolve client escalations. Collaborate with quantitative analysts, product managers, and engineering teams to improve automation, data reliability, and analytical accuracy.
Summary Generated by Built In

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.

I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

Skills Required

  • Bachelor’s or Master’s degree in Finance, Economics, Data Science, Computer Science, or a related quantitative field
  • At least 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
  • Proficiency in SQL
  • Experience developing QA frameworks for large datasets and complex analytics
  • Familiarity with data validation techniques, anomaly detection, and root cause analysis
  • Understanding 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
  • Proficiency in coding and reviewing production-level code in Python or R
  • Familiarity with Morningstar data models and their end-to-end lifecycle

What the Team is Saying

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Morningstar Compensation & Benefits Highlights

  • Retirement Support — Employer 401(k) matching and access to Morningstar retirement‑planning tools are prominent features of the package. These elements create a strong foundation for long‑term savings.
  • Leave & Time Off Breadth — Flexible time off, paid holidays, sick and personal days, and a paid sabbatical every four years provide generous time away from work. Sabbaticals are specifically highlighted as a standout perk.
  • Parental & Family Support — A global minimum of 16 weeks for primary caregivers, up to eight weeks for secondary caregivers, and at least six weeks of paid caregiving leave offer robust family support. Some materials also note adoption assistance and related resources.

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The Company
HQ: Chicago, IL
11,500 Employees
Year Founded: 1984

What We Do

We are a global investment research and financial data company with 40-plus offices across North America, Europe, Australia, and Asia. Our products and services are used daily by individual investors, financial advisors, asset managers, retirement plan providers, and institutional investors. We provide data, research, and analysis across managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. The financial system can have real barriers—hidden information, friction that can slow decisions, and forces that can limit transparency and access. We work to remove them, bringing independent research, connected data, and investor-first tools to a system that needs more clarity. The people doing this work span research, technology, design, product, sales, and functional areas. We build many of our products in-house, so the work can connect directly to the tools investors use to make real financial decisions.

Why Work With Us

Morningstar’s missing is to empower investor success. We can only do that if our people feel empowered. That means finding people who think independently, bring a wide range of backgrounds with analytical rigor and genuine intellectual curiosity to the work.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.

Typical time on-site: 4 days a week
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