SVP, Finance Data Analytics

Role Overview

• Define and drive the long-term product vision and strategy for financial data profiling and AI tools, ensuring alignment with organizational goals for financial control, reconciliation, and advanced analytical capabilities.
• Proactively identify and assess market trends, emerging AI/ML technologies, and automation opportunities to enhance data discovery testing and substantiation processes.
• Translate complex business requirements related to financial ledger data discovery, reconciliation/proving, workflow optimization, and data analytics into a clear, actionable product roadmap.
• Formulate and set strategic direction for processes, organization, and architecture covering Finance across Citi businesses, products, functions, and locations.
• Develop and manage the product lifecycle for data discovery and reconciliation tools, enforcing and delivering solutions that accurately depict data elements, structures, processes, and differences between legacy and target finance ledger systems.
• Drive the enhancement of workflow processes and data analytics capabilities, leveraging AI/ML for anomaly detection, data matching, and predictive insights in financial data.
• Participate in assessing and incorporating changing business, regulatory, and market information needs into finance processes and applications.
• Liaison between business stakeholders (finance, controllers, reporting teams), technology teams (data engineering, AI/ML specialists), and external partners.
• Lead improvement for the Strategic Ledger tooling.
• Ensure all data discovery, reconciliation products, and AI tools strictly adhere to financial and regulatory reporting standards and internal compliance frameworks, demonstrating the integrity of financial books and records through testing and substantiation.
• Oversee the integration of compliance and audit requirements directly into the product design and delivery process, focusing on transparent and auditable reconciliation outcomes.

Requirements

• 10+ years of relevant experience, preferably within the financial services industry.
• In-depth knowledge of financial books and records, consolidated ledger reporting, and the intricacies of reconciliation processes between diverse financial systems, within a global financial institution.
• Expertise in designing and implementing advanced data analytics solutions, workflow automation, and integrating AI/ML models for financial data processing, comparison, and reconciliation.
• Experience with Python, KNIME, Generative/Agentic Artificial Intelligence applications (preferably in an implementation role).
• Demonstrated ability to perform complex data analysis, identify patterns, quantify differences, and derive actionable insights from large financial datasets.
• Demonstrated ability to define product strategy, develop roadmaps, and drive execution in complex, fast-paced environments, with a focus on delivering AI-enabled data utility tools for financial reconciliation.
• Exceptional written and verbal communication, negotiation, and stakeholder management skills, with proven ability to deliver compelling presentations and engage effectively with C-Suite leaders.
• Proven ability to implement and manage data lineage, robust data quality frameworks, and exception resolution processes for critical financial reconciliation data.
• Proficiency in product management tools (e.g., JIRA, Confluence) and agile development methodologies.
• In-depth knowledge of banking products and systems is highly preferred.

Tech Stack

• Python

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