AI-Data Solutions Lead -Vice President

AI-Data Solutions Lead
-Vice President

Job Req :

Location(s):
Mumbai, Maharashtra, India

Job Type: Hybrid

Posted:
May. 20, 2026

As a Vice President Data Analyst in the Enterprise Data Office Data Solutions team based in our Mumbai office, you will play a critical leadership role in shaping our Enterprise Risk Management data as an asset strategy. This position demands a seasoned professional with deep expertise in data analytics, a proven track record in applying advanced AI/ML techniques in solving business problems, and exceptional leadership skills to drive strategic initiatives, mentor a high‑performing team, and deliver impactful, executive‑level presentations.

You will be instrumental in advancing our data solutioning and analytics capabilities within a dynamic global financial environment.

• Data Solutions Delivery:
  • Provide expertise on Data Governance and/or Data Risk and Controls framework including design, effectiveness, performance monitoring and self‑assessment processes
  • Oversight and analysis of data‑related issues, tracking of ownership and target dates and associated metrics and reporting; lead and mentor a team of junior data analysts, fostering their professional growth, developing their technical and soft skills, and ensuring high‑quality, impactful deliverables
  • Drive the adoption of best practices in data analysis, data governance, and project management across the team and contribute to a culture of continuous improvement
• Leadership & Mentoring:
  • Lead and mentor a team of junior data analysts, fostering their professional growth, developing their technical and soft skills, and ensuring high‑quality, impactful deliverables
  • Drive the adoption of best practices in data analysis, data governance, and project management across the team and contribute to a culture of continuous improvement
• AI/Advanced Analytics Strategy & Implementation:
  • Spearhead the integration and advanced application of Agentic AI, LLM, and other Generative AI (GenAI) tools to develop sophisticated and innovative data analytical solutions for Enterprise Risk Management
  • Define, develop, and implement AI/ML strategies for predictive modeling, advanced anomaly detection, automated reporting, and enhanced risk insights within the financial risk domain
  • Evaluate and recommend new AI/ML technologies and methodologies to continuously improve data analysis and reporting capabilities
• Strategic Impact & Executive Presentations:
  • Proactively identify strategic data opportunities and challenges, proposing innovative solutions to enhance Enterprise Risk Management capabilities and reporting effectiveness
  • Prepare and deliver compelling, standout presentations and strategic updates to senior management, global stakeholders, and internal forums, translating complex data insights into clear, concise, and actionable recommendations
• Core Data Analysis & Governance:
  • Provide in‑depth leadership in system and data analysis to support Enterprise Risk Management data initiatives, ensuring strict alignment with Citi’s data governance policies (CDGP) and standards (CDGS) framework
  • Oversee the comprehensive gathering and documentation of Business Requirements Documents (BRDs) and Functional Requirements Documents (FRDs) for complex data‑centric projects, including detailed specifications for data quality rules, data lineage, and data layer components, partnering closely with technology teams to ensure robust implementation
  • Actively manage, update, and ensure timely resolution of project artifacts, tasks, issues, and action items within JIRA or similar project‑management tools, maintaining accurate tracking of progress and dependencies
  • Contribute strategically to the design, documentation, and maintenance of logical and physical data layers, including advanced data models, data dictionaries, and data lineage, to ensure robust, scalable, and efficient data solutions for Enterprise Risk Management
  • Lead efforts to identify, analyze, and troubleshoot complex data quality gaps and issues, collaborating with business data owners and technology teams to propose and implement effective remediation strategies and monitoring routines
  • Rigorously review and…