Manager, VIK Data and Systems

The Manager will play a critical role in evaluating complex AI, data, and analytics initiatives. This role requires partnering with cross‑functional teams—including engineering, data science, product, compliance, and Finance—to translate ambiguous business needs into structured, analytically grounded requirements. The role is responsible for conducting deep‑dive analysis, identifying risks across data and workflow dependencies, and ensuring high‑quality execution of use‑case reviews that enhance decision‑making, strengthen governance, and accelerate innovation.

This role requires exceptional analytical skills, strong stakeholder influence, and the ability to simplify complexity while maintaining analytical rigor, consistent with Visa’s expectations for data‑driven leadership.

• Lead end‑to‑end analysis of data use cases by identifying and documenting risks, engaging the right subject‑matter experts, and synthesizing insights into clear, actionable recommendations.
• Lead Discovery & Design: map business processes and identify automation opportunities.
• Collaborate with AI engineers, analysts, UX teams, data scientists, and regional partners to align requirements, clarify dependencies, and drive unified execution.
• Identify and design innovative, data‑driven approaches that unlock new insights and solve high‑impact business problems.
• Moves with urgency and clarity, quickly breaking down complex problems and driving forward progress even when information is incomplete.
• Anticipates roadblocks early and resolves them decisively, keeping projects moving and stakeholders aligned.
• Analyze complex datasets to form well‑reasoned recommendations and deliver actionable insights that directly address stakeholder needs.
• Establish and enforce rigorous data‑quality standards by validating inputs, identifying anomalies, and ensuring all analyses are grounded in accurate, trusted datasets.
• Own reconciliation workflows across multiple data sources verifying consistency, tracing discrepancies to root causes, and partnering with engineering or system owners to drive timely resolution.
• Design repeatable, automated checks to continuously monitor data accuracy, ensuring stakeholders can rely on timely, precise, and high‑signal insights.
• Surface data‑quality risks early, assess their business impact, and drive cross‑functional actions that maintain accuracy across fast‑evolving datasets and processes.
• Influence decision‑making by distilling analytical findings into concise recommendations
• Ensure strong partnership alignment across teams to maintain roadmap clarity, execution quality, and business relevance.
• Continuously evaluate and refine analytical processes, documentation standards, and review workflows.
• Drive operational discipline around prioritization, risk mitigation, and execution in ambiguous environments.
• Identify and document risks related to data quality, model feasibility, business logic, process scalability, and regulatory considerations.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• Strong data‑diagnostics capability, with the ability to investigate anomalies, perform root‑cause analysis, and reconcile data across multiple systems with precision.
• Demonstrated ability to move quickly from problem identification to action, driving momentum.
• Thrives in fast‑paced, evolving contexts, adapting priorities in real time.
• Expertise in translating ambiguous business questions into structured analytical frameworks, clearly defining metrics, requirements, and expected outcomes.
• Strong consultative skills, able to deeply understand stakeholder needs, pressure‑test assumptions, and guide partners toward data‑driven decisions.
• Excepti…