Analytics and Data Science Data Rules and Exception Management Director

Citi • Tampa, FL

175d • $170,000 - $300,000

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Drive the implementation of advanced statistical and analytical methods, including machine learning and predictive modeling, to detect anomalies and uncover underlying patterns.
• Leverage data profiling and predictive modeling to forecast trends, rules refinement, and risk factors that could potentially impact the business.
• 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.
• 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 engagement with regulatory bodies, effectively assisting the firm in its communication of remediation status and managing stakeholder expectations during regulatory reviews and audits.
• Engage senior stakeholders to influence priorities, secure alignment, and drive adoption of the Data Quality framework and tools.
• Partner with internal audit, compliance, finance, and risk management functions to validate data governance controls and evidence regulatory compliance.
• Mentor and develop talent within the data science team, promoting a culture of continuous learning, collaboration, and innovation.

Benefits

• Medical, dental & vision coverage
• 401(k)
• Life, accident, and disability insurance
• Wellness programs
• Paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees