Job Description

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

Skills and Competencies

• 5+ years of relevant experience in data operations, data management, data quality, analytics, automation, or a related role
• Strong expertise in SQL and Python, with the ability to analyze large datasets, automate workflows, and generate actionable insights
• Proven experience in data quality management, including profiling, anomaly detection, and implementing scalable remediation processes
• Solid understanding of data architecture, data modeling, ETL/ELT workflows, and data integration across multiple systems
• Hands-on experience with analytics and visualization tools such as Databricks, and Power BI (or similar platforms)
• Excellent problem-solving and analytical skills, with the ability to identify root causes and translate findings into impactful solutions
• Strong communication and collaboration skills, with the ability to engage both technical and non-technical stakeholders in a global environment

Education

• Bachelor’s or Master’s degree in Data Science, Information Systems, Computer Science, Data Management, Economics, Finance, Mathematics, Statistics, or a related field

Responsibilities

• Drive data quality initiatives by monitoring, measuring, and enhancing the accuracy, consistency, and reliability of large-scale datasets
• Investigate data issues, identify patterns and root causes, and lead remediation efforts through structured, repeatable processes
• Optimize data operations by introducing automation, controls, and scalable frameworks to improve efficiency and reduce manual effort
• Partner with technology teams to support data integration, pipelines, and data models, ensuring seamless and reliable data delivery
• Leverage analytics tools to generate insights, track quality trends, and communicate progress to key stakeholders
• Collaborate cross-functionally with Product, Content, Sales, and global data teams to align priorities and deliver business impact
• Develop and maintain clear documentation for data processes, quality rules, and governance frameworks to enable scalability and consistency

About the Team
You will be part of a global, collaborative data team focused on delivering high-quality, trusted data that powers Moody’s flagship Orbis platform and related solutions. The team works at the intersection of data, technology, and business, driving innovation through automation, advanced analytics, and continuous process improvement. By joining us, you will have a unique opportunity to work on large-scale data challenges, influence global data strategy, and contribute to meaningful insights.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.