Analytics & Data Science Data Rules & Exception Management Director (Hybrid)

About Citi

Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients.

Citi’s Mission and Value Proposition explain what we do and Citi Leadership Standards explain how we do it. Our mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We strive to earn and maintain our clients’ and the public’s trust by constantly adhering to the highest ethical standards and making a positive impact on the communities we serve. Our Leadership Standards is a common set of skills and expected behaviors that illustrate how our employees should work every day to be successful and strengthens our ability to execute against our strategic priorities.

The Enterprise Data Office (EDO) organization drives and enforces data quality across Citi. The EDO will define and enforce data-related policies and standards across Citi and equip the firm with the tools required to take ownership and accountability for data governance and management. This is achieved through setting the Citi Data Governance Policy (CDGP), defining Citi Data Governance Standards and providing a governance framework for data ownership and data quality throughout Citi. The EDO is the sponsor for the overall data quality program at Citi and associated Board reporting.

Job Summary

This senior leadership role is pivotal in leveraging advanced analytics and data science to drive enterprise-wide data quality and integrity. The Director will employ a data-driven approach to rigorously assess data quality rules, identify patterns, and predict downstream implications, enabling precise and effective decision-making. The role demands strong analytical acumen to pinpoint data anomalies, perform root cause analysis, and translate complex data insights into tangible remediation strategies and continuous improvement. Collaborating across data domains, this individual will ensure data fit-for-purpose and embed sustainable, analytically driven data quality practices, ultimately shaping how data quality is measured, monitored, and optimized across intricate data environments for enhanced trust and operational integrity.

Capabilities:

• Data Quality Analytics, Trend Analysis, and Predictive Modeling:
  • Drive the implementation of advanced statistical and analytical methods, including machine learning and predictive modeling, to detect anomalies, and uncover underlying patters.
  • Leverage data profiling and predictive modeling to forecast trends, rules refinement, and risk factors that could potentially impact the business
  • Stay abreast of emerging trends across the data landscape, identifying patterns and trends in data that could drive innovation or improve operational efficiency.
• Data Quality & Compliance:
  • Support the development, implementation, and continuous refinement of data quality rules specific to finance datasets, ensuring alignment with regulatory standards such as GDPR, SOX, and other applicable compliance frameworks. 
  • Develop and deliver reporting to support detailed analysis of finance data quality to support identification of issues, root causes, and actionable remediation strategies. 
  • Establish robust reporting and dashboards to track, trend, and communicate data quality and data quality process metrics, highlighting alignment to SLAs, alignment to data quality thresholds, and areas for improvement. 
  • Provide reporting and analytics to support data quality validation and cleansing processes to minimize data discrepancies and ensure accuracy in financial reporting.
• Exception & Break Management:
  • Develop and implement frameworks to identify, analyze, and resolve exceptions and breaks in data systems, such as reconciliation discrepancies, transactional inconsistencies, or reporting anomalies.
  • Design automated solutions to detect and address breaks or anomalies proactively, ensuring minimal business disruption.
  • Support and enable the use of data insights from key enabling technologies including data catalog, data lineage, data quality rules engines, exception workflow, and underlying reporting capabilities. 
• Data Governance & Regulatory Reporting
  • Support engagement with regulatory bodies, effectively assisting the firm in its communication of remediation status and managing stakeholder expectations during regulatory reviews and audits. 
  • Understand end use case requirements for data pipelines, e.g., financial regulatory reporting requirements and critical business processes, and assist in the management and oversight of data quality exception health supporting these pipelines. 
• Strategic Data Quality Leadership:
  • Engage senior stakeholders to influence priorities, secure alignment, and drive adoption of the Data Quality framework and tools.
  • Provide strategic direction on the application of analytics to improve data quality for datasets across the firm in support of management reporting, risk management, and regulatory compliance, including direction and insight into reporting and trending.
• Audit & Risk Partnership:
  • Partner with internal audit, compliance, finance, and risk management functions to validate data governance controls and evidence regulatory compliance.
• Team & Capability Development:
  • Mentor and develop talent within the data science team, promoting a culture of continuous learning, collaboration, and innovation, while fostering cross-functional collaboration between technology, finance, and operations teams to ensure data alignment and integrity.

Qualifications:

The role requires strong analytical, interpersonal and leadership skills that rely on influence and building effective partnerships to execute on our delivery plans and controls in a systematic, measurable, and effective way.

• 10+ years of experience in data science, data engineering, analytics, or a related field within the financial services industry.
• Proven experience managing complex data projects, particularly in financial data rule enforcement and exception management.
• Strong understanding of financial data structures, regulations, and market mechanics.
• Deep expertise in programming languages required (examples: Python, R, SQL, Java, Ruby, Rust).  
• Strong statistical math skills required (examples: linear algebra, calculus and statistics are needed for Time Series Forecasting). 
• Expertise in programming applications (e.g., Python, R, SQL), and databases (e.g. Hadoop)
• Skilled with data governance solutions (e.g., Collibra, Alation, Manta, Ab Initio, etc.)  and financial software (e.g., Bloomberg, Reuters).
• Developed visual dashboards (examples: D3, Altair, Matplotlib, Tableau, Power BI).
• Experience with data governance and data quality management, particularly in relation to financial datasets.
• Advanced proficiency in predictive modeling, machine learning, and statistical analysis.

A successful candidate will have the following attributes:

• Leadership experience with the ability to manage cross-functional teams and deliver complex projects.
• Strong strategic thinking and decision-making skills.
• Excellent problem-solving ability, particularly in high-pressure financial environments.
• Exceptional communication skills, with the ability to present complex analytical insights to senior executives and non-technical stakeholders.

Education:

• Bachelor's degree/University degree or equivalent experience
• Master's degree preferred

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Job Family Group:

Data Governance

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Job Family:

Data Governance Foundation

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Time Type:

Full time

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Primary Location:

Irving Texas United States

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Primary Location Full Time Salary Range:

$170,000.00 - $300,000.00

In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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Most Relevant Skills

Constructive Debate, Data Governance, Data Management, Data Quality, Internal Controls, Management Reporting, Policy and Procedure, Program Management, Risk Controls and Monitors, Risk Management.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Anticipated Posting Close Date:

Sep 05, 2025

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

 

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