Visa is a global payments technology company that connects consumers, businesses, banks and governments in more than 200 countries and territories, enabling them to use digital currency instead of cash and checks.

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Role Summary

The Analyst will support Visa Consulting & Analytics client engagements by conducting quantitative and qualitative analysis, developing data-driven insights, and contributing to clear, structured client deliverables. This role is ideal for early‑career professionals with strong analytical skills who are eager to grow within a consulting and analytics environment under guidance from senior team members.

Analytics & Problem Solving

• Execute quantitative and qualitative analyses with guidance from Managers and Senior Managers.
• Perform data exploration, filtering, and validation to extract meaningful insights from complex datasets.
• Break down client problem statements into structured analytical components to support hypothesis-driven analysis.

Insight Development & Storytelling

• Translate analytical findings into clear, data-supported takeaways (focused on insights rather than recommendations).
• Contribute to developing logical storylines that connect data, insights, and business context.
• Ensure high standards of data quality, accuracy, and analytical rigor.

Client Deliverables & Project Support

• Use and adapt standardized consulting templates to address unique client needs while maintaining clarity and structure.
• Support the creation of client-ready presentations and materials that clearly articulate key messages.
• Leverage data and insights to support project management and internal decision-making

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

Qualifications

• Bachelor’s degree in Economics, Finance, Business, Statistics, Data Analytics, Engineering, or a related quantitative field.
• Strong analytical and problem-solving skills with the ability to work with structured datasets.
• Ability to extract basic insights and conclusions from quantitative analysis.
• Clear written and visual communication skills (e.g., slides, charts, summaries).
• Strong attention to detail, accuracy, and data quality.
• Ability to collaborate effectively in a team-based consulting environment and incorporate feedback.

Preferred Qualifications

• Exposure to consulting, financial services, payments, or technology environments.
• Experience with Excel and PowerPoint; familiarity with SQL, Python, Tableau, or Power BI is an advantage.
• Demonstrated interest in payments, digital finance, or analytics-driven strategy.

• Execute quantitative and qualitative analyses with guidance from Managers and Senior Managers.
• Perform data exploration, filtering, and validation to extract meaningful insights from complex datasets.
• Break down client problem statements into structured analytical components to support hypothesis-driven analysis.
• Translate analytical findings into clear, data-supported takeaways (focused on insights rather than recommendations).
• Contribute to developing logical storylines that connect data, insights, and business context.
• Ensure high standards of data quality, accuracy, and analytical rigor.
• Use and adapt standardized consulting templates to address unique client needs while maintaining clarity and structure.
• Support the creation of client-ready presentations and materials that clearly articulate key messages.
• Leverage data and insights to support project management and internal decision-making

• Strong analytical and problem-solving skills
• Ability to work with structured datasets
• Ability to extract basic insights and conclusions from quantitative analysis
• Clear written and visual communication skills
• Strong attention to detail, accuracy, and data quality
• Ability to collaborate effectively in a team-based consulting environment and incorporate feedback
• Experience with Excel and PowerPoint
• Familiarity with SQL, Python, Tableau, or Power BI is an advantage

• Bachelor’s degree in Economics, Finance, Business, Statistics, Data Analytics, Engineering, or a related quantitative field.
• Exposure to consulting, financial services, payments, or technology environments.
• Demonstrated interest in payments, digital finance, or analytics-driven strategy.