Senior Data Scientist – Executive Reporting

About the role

Mastercard is seeking a highly analytical Senior Data Scientist to lead enterprise‑level KPI reporting, business performance tracking, and strategic analytics across global business units. The role will own end‑to‑end analytics solutions, from requirement gathering to commercialization, partnering with finance, FP&A, and technology teams.

Key responsibilities

• Own and manage executive‑level KPI reporting across multiple products, regions, and business units.
• Design scalable KPI measurement frameworks, reporting methodologies, and governance processes.
• Develop and maintain dashboards and analytics solutions using Tableau, Power BI, SQL, and Python.
• Drive automation initiatives to improve reporting efficiency, data accuracy, and operational scalability.
• Lead finance automation projects that transform manual FP&A reporting into governed, role‑based dashboards.
• Partner with global stakeholders to gather requirements, resolve reporting issues, and deliver actionable insights.
• Monitor data quality, perform validations, and ensure accuracy of business‑critical reporting.
• Translate complex business problems into data‑driven and AI‑enabled solutions for senior leadership.
• Evaluate, integrate, and champion Generative AI and AI capabilities within existing products.
• Mentor team members on technical tools, analytics best practices, and AI adoption.

Required profile

• 4+ years of experience in data analytics, business intelligence, data science, or product analytics.
• Proven ability to design and manage enterprise‑level KPI frameworks and automate finance/FP&A reporting.
• Strong understanding of AI/ML, Generative AI concepts, LLMs, RAG architectures, and prompt engineering.
• Experience integrating AI capabilities into business products and analytical solutions.
• Excellent stakeholder management and communication skills across global teams and senior leadership.
• Demonstrated ability to lead projects independently and manage multiple priorities.

Required skills

• Tableau
• Power BI
• SQL
• Python
• AI/ML concepts
• Generative AI, LLMs, RAG architectures
• Prompt engineering
• API integration
• Data modeling and validation
• Reporting governance