Assistant Director - Data Specialist

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.

• Strong technical expertise in SQL and Python for data analysis, validation, and remediation, enabling accurate and scalable data operations
• Proven experience in data quality management and remediation processes, ensuring completeness, consistency, and reliability of large datasets
• Ability to operate in fast-paced, client‑facing environments, managing competing priorities and delivering against tight deadlines and service level agreements
• Experience coordinating cross‑functional stakeholders and contractor resources to maintain operational continuity and quality output
• Knowledge of data processing frameworks, including ETL pipelines, data integration, and data modeling (experience with Databricks or Spark preferred)
• Strong analytical and problem‑solving skills with the ability to communicate clearly to both technical and non‑technical stakeholders
• 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

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field

Deliver high‑quality data remediation and operations support, ensuring accurate, timely, and scalable data solutions in a client‑facing environment.

• Act as a primary point of contact for data remediation issues, triaging, prioritizing, and resolving critical client‑facing data incidents
• Execute remediation activities using SQL and Python to analyze, validate, and improve data quality across multiple datasets
• Monitor and enhance data quality by ensuring accuracy, completeness, and consistency through structured processes and controls
• Execute data workflows, pipelines, and integration processes to support efficient and reliable data operations
• Identify and implement opportunities for automation and process improvements to enhance operational efficiency
• Coordinate contractor resources, including task allocation, onboarding support, and quality oversight to ensure consistent delivery
• Track remediation activities, maintain documentation, and monitor progress against timelines, service levels, and operational targets
• Produce operational reporting on volumes, trends, risks, and performance metrics to support decision‑making
• Collaborate with cross‑functional teams to address root causes, improve remediation playbooks, and align with data strategy objectives
• Escalate complex or high‑risk issues with structured insights and recommendations to support timely resolution

Our Data Estate team is responsible for delivering high‑quality, trusted commercial data products to clients globally. The team contributes to Moody’s by providing comprehensive and reliable data solutions that support critical business decisions, while driving data quality and operational excellence through scalable remediation and governance practices. It also enhances the accessibility and usability of data through efficient processing,…