Data Quality Analytics and Reporting Lead

The Data Quality Analytics & Reporting Lead Analyst is responsible for delivering subject matter and industry expertise across the enterprise in coordination with the Data Quality Analytics & Reporting team. The overall objective is to manage and execute continuous Data Quality by overseeing firm-wide controls, setting parameters and guidelines for measurement, evaluation, adoption, and communications of Data Quality and Data Quality risk.  Requires in-depth understanding of data and reporting.  Requires sound analytical skills to filter, prioritize and validate potentially complex and dynamic material from various sources to monitor and certify authoritative data sources and remediate data concerns.

Design, implement, and manage enterprise-wide data quality frameworks, including the definition of data quality rules and comprehensive scorecards. Develop and deploy preventative and detective data controls across the entire data lifecycle and critical data flows for Enterprise Risk Data. Drive the integration of data quality controls directly into upstream systems and data pipelines to ensure quality at source. Leverage advanced AI/Machine Learning techniques for anomaly detection, real-time data monitoring, and predictive identification of data quality issues. Utilize Generative AI solutions for metadata enrichment, automated reporting, and process automation within the data ecosystem. Lead the end-to-end lifecycle of data issues, from identification and root cause analysis (RCA) through resolution, fix implementation, and closure verification. Focus on delivering root-cause, scalable, and sustainable fixes to prevent recurrence of data issues. Lead and execute Data Quality Control Assessments to validate the effectiveness of implemented controls. Evaluate the efficacy and operational performance of data controls across end-to-end data flows. Provide robust support and documentation for internal and external audit requirements and regulatory reviews. Cultivate strong partnerships with Business, Technology, AI, Risk, and Data teams to align strategies and foster collaborative outcomes. Drive continuous process re-engineering initiatives aimed at improving upstream data quality and overall data management efficiency. Influence and advocate for the adoption of leading data governance and AI practices across the enterprise. Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. Recommended Qualifications :  6+ years of progressive experience in Data Governance, Data Quality, Data Controls, or Regulatory programs within a complex enterprise environment. Understanding of AI/Machine Learning and Generative AI use cases specifically within data management and analytics. Familiarity with data lineage, metadata management, and AI governance principles. Proven track record of strong stakeholder management and influencing skills across diverse organizational levels. Ability to navigate complex organizational structures and drive impactful outcomes.

Bachelor's/University degree, Master's degree preferred This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. ------------------------------------------------------ Job Family Group: Data Governance ------------------------------------------------------ Job Family: Data Quality & Data Quality Analytics and Reporting ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location Full Time Salary Range: $111,600.00 -