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Finance Data Analytics and Utility - SVP

Citigroup

Finance Data Analytics and Utility - SVP

Citigroup

TAMPA, Florida, United States of America; GETZVILLE, New York, United States of America

·

On-site

·

Full-time

·

3w ago

Responsibilities may include staff management, resource allocation, and work distribution within the team. Workflow Enhancement & Data Analytics Participate in assessing and incorporating changing business, regulatory, and market information needs into finance processes and applications. Provide advice to internal clients on the implications of business trends, issues, operating environment changes, and firm or business unit strategy. 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. 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. 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. Leverage expertise in AI/ML frameworks, workflow automation platforms, and advanced data analytics tools to optimize the identification, analysis, and resolution of reconciliation differences. Explore and integrate cutting-edge AI-powered solutions for scalable and intelligent financial data utility. Possess a strong understanding of financial data architecture, data modeling, and advanced data analytics techniques. Guide the implementation of robust data controls, data lineage, tracing, and data quality rules specifically for comparative analysis and reconciliation processes. Experience: 10+ years of relevant experience, preferably within the financial services industry. Financial Books & Records Expertise: 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. Data Utility & AI Technologies: 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). Strong Data Analytics Skills: Demonstrated ability to perform complex data analysis, identify patterns, quantify differences, and derive actionable insights from large financial datasets. Strategic Planning & Execution: 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. Leadership & Communication: Exceptional written and verbal communication, negotiation, and stakeholder management skills, with proven ability to deliver compelling presentations and engage effectively with C-Suite leaders. Data Governance & Quality: Proven ability to implement and manage data lineage, robust data quality frameworks, and exception resolution processes for critical financial reconciliation data. Product Management Tools & Methodologies: Proficiency in product management tools (e.g., JIRA, Confluence) and agile development methodologies. Banking Products/Systems: In-depth knowledge of banking products and systems is highly preferred. Bachelor's degree required; Master's degree preferred. Accounting / Auditing background preferred. Assessment, Change Management, Communication, Credible Challenge, Management Reporting, Problem Solving, Program Management, Risk Management, Stakeholder Management, Strategic Planning. ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Anticipated Posting Close Date: Feb 18, 2026 ------------------------------------------------------

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About Citigroup

Citigroup

Citigroup

Public

Citigroup Inc. or Citi is an American multinational investment bank and financial services company based in New York City. The company was formed in 1998 by the merger of Citicorp, the bank holding company for Citibank, and Travelers; Travelers was spun off from the company in 2002.

10,001+

Employees

New York City

Headquarters

Reviews

3.3

4 reviews

Work Life Balance

3.0

Compensation

3.2

Culture

2.8

Career

2.5

Management

2.7

35%

Recommend to a Friend

Pros

Compensation increases for investment banking roles

Legitimate investment banking employer

Internship opportunities available

Cons

Unclear career progression paths

Limited meaningful experience in internships

Compensation raises lower than competitors

Salary Ranges

28 data points

Mid/L4

Senior/L5

Staff/L6

Mid/L4 · Business Risk Intermediate Analyst

1 reports

$77,165

total / year

Base

$67,100

Stock

-

Bonus

-

$77,165

$77,165

Interview Experience

5 interviews

Difficulty

2.8

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 40%

Negative 60%

Interview Process

1

Application Review

2

Recruiter Screen

3

Programming Assessment

4

Hiring Manager Interview

5

Panel/Superday Interviews

6

Final Decision

Common Questions

Technical Knowledge

Case Study

Behavioral/STAR

Past Experience

Culture Fit