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.

Employment eligibility to work in the U.S. is required, as Moody's will not pursue visa sponsorship for this position now or in the future

Skills and Competencies

• Experience working with Agile product development processes
• Prior technical business analyst or technical product management level knowledge
• Prior experience analyzing and/or designing relational and non-relational data sets, especially in financial data, commercial real estate data, public registration and regulatory data, structured and semi-structured news data, and the relationships between entities in such datasets
• Experience and proficiency using SQL for data analysis, or similar AI enabled platforms
• Experience partnering with Legal, Risk, and Data Governance stakeholders to ensure data privacy compliance and proactively mitigate regulatory, operational, and data misuse risks
• Experience working in a matrixed environment and navigating multiple stakeholders to drive alignment
• Outstanding verbal and written communication skills
• Superb analytical skills and persistence in problem solving
• Demonstrated initiative, enthusiasm to learn, excel and be a part of a dynamic team
• Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency. Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use

Education

Undergraduate/first-level degree (e.g., Bachelor's) or graduate/second-level degree (e.g. MBA, Master's) with an emphasis in finance, economics, computer science, data science, or related fields

Responsibilities

The Director of Data Governance - Data Modeling will play a pivotal role within Moody's Analytics Data Estate Data Governance team. This position is responsible for designing, coordinating the review process, and maintaining comprehensive documentation for data models at all levels-conceptual, logical, and physical. The Director will collaborate closely with technology and application development teams to ensure data models are well-documented, accurate according to the policies and standards set by Data Stewards, and consistently updated to support evolving business and customer requirements.

This role enables teams to better understand and utilize foundational data structures, by fostering transparency and clarity in data modeling documentation, ultimately supporting data-driven decision-making and operational excellence.

• Serve as the accountable owner of the Data Estate Logical Data Model (LDM) across all domains, maintaining a single, authoritative source for entities, relationships, attributes, and their justifications. Ensure the LDM accurately reflects customer and product perspectives, and manage all changes through a governed, auditable process

• Translate business use cases into scalable modeling requirements by reviewing and validating workflows provided by Data Stewards, abstracting their inputs into reusable modeling patterns, and identifying common entities, standardized relationships, and consistent attribute definitions across domains

• Maintain conceptual integrity by ensuring entities and classifications are consistent across data stores and consumption points such as data feeds, API endpoints, and user interfaces. Address structural modeling issues like duplicate concepts, inconsistent use of entity types and attributes, and overloaded fields representing multiple real-world concepts

• Define and manage the relationship model by establishing clear types, cardinality, directionality, and temporal behavior, ensuring relationships accurately represent real-world constraints rather than system limitations. Prevent inconsistencies across domains and maintain thorough justifications so relationships can be clearly explained to customers, withstand audits, and be reliably utilized by AI systems

• Establish modeling standards for Data Stewards by defining clear criteria for steward-proposed changes, publishing guidelines on entity creation, attribute versus entity decisions, and relationship semantics, and rigorously reviewing outputs for structural accuracy, alignment with enterprise patterns, and long-term scalability

• Provide Data Quality teams with guidance on critical entities, essential relationships and attributes across domains. Ensure that data quality rules are firmly rooted in the semantics of the data model, and review QA approaches to guarantee alignment with modeling intent rather than just technical implementation

• Ensure the Data Estate Logical Data Model is AI-ready and interoperable by supporting stable identifiers, explicit relationships, and rich, explainable semantics. Define and implement modeling standards necessary for advanced AI applications such as Retrieval-Augmented Generation (RAG), Generative AI, and agentic workflows, proactively identifying and addressing model gaps that could lead to hallucinations, misinterpretations, or incorrect reasoning, in collaboration with governance and platform teams

• Collaborate with stakeholders to resolve conceptual conflicts among domains, products, and legacy systems. Ensure all changes and their rationale are communicated effectively to Data Stewards, Engineering, Product, and customer-facing teams

• Establish strong and collaborative relationships with business partners to help identify gaps in existing data models and design new data models to support application interfaces, workflows and monitoring and reporting usage

About the team

The Moody's Data Governance team operates as a central capability within the Data Estate, focused on ensuring data is fit for purpose, trusted, and aligned to customer use cases across Moody's Analytics. The team defines and enforces data governance standards by identifying critical data elements, designing logical data models, documenting lineage, and establishing field-level data quality policies that reflect how customers actually use the data. Organized around domain-based data steward pods and supported by shared functions such as QA design, metadata management, entitlements, and customer engagement, the team works closely with product, engineering, and data operations to clarify accountability, reduce overlap, and improve decision-making. Through this operating model, Data Governance drives higher data quality, transparency, and interoperability, while enabling scalable analytics, regulatory compliance, and AI-ready data across the enterprise.

For US-based roles only: the anticipated hiring base salary range for this position is $151,000.00 - $218,950.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody's also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.

Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody's also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Click here to view our full EEO policy statement. Click here for more information on your EEO rights under the law. Click here to view our Pay Transparency Nondiscrimination statement. Click here to view our Notice to New York City Applicants.
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.