Job Description
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we are helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
About The Role
The People Analyst will be a key member of the Regional People Data & Analytics team, delivering workforce insights, analytics, and strategic decision support across multiple business units globally. This role combines analytics, data management, reporting, program management, and emerging AI capabilities to enable data-driven talent decisions across Mastercard. The ideal candidate is a detail-oriented problem solver with strong SQL and data modeling expertise, a passion for data quality, and an interest in leveraging Generative AI to improve workforce analytics and business outcomes. This individual will help transform complex people data into actionable insights while driving consistency, scalability, and innovation across reporting and analytics solutions.
Key Responsibilities
Workforce Analytics & Reporting
Serve as the primary point of contact for operational reporting, workforce metrics, and analytics requests from global stakeholders.
Partner with business leaders to understand underlying business challenges and translate them into actionable analytical solutions.
Collaborate with the Financial Planning & Analysis (FP&A) CoE to support monthly headcount reporting, forecasting, and workforce analysis.
Develop and maintain dashboards, reports, and visualizations that provide meaningful workforce insights.
Data Management & Quality
Ensure the accuracy, consistency, and integrity of workforce data across systems and reporting solutions.
Partner with HR Systems, Data Management, and Engineering teams to identify and resolve data quality issues.
Establish controls and validation processes to improve trust and reliability of workforce metrics.
Drive data governance standards and ensure compliance with privacy and security requirements for people data.
Data Modeling & Analytics Engineering
Design and maintain scalable analytical data models to support reporting, self-service analytics, AI use cases, and workforce planning.
Apply dimensional modeling principles and create efficient data structures for workforce analytics.
Leverage SQL to query, analyze, validate, and optimize large and complex datasets.
Collaborate with Data Engineers and Analysts to improve analytical data foundations and reporting capabilities.
AI & Innovation
Explore and leverage Generative AI solutions to improve reporting efficiency, automate insights generation, and enhance workforce analytics.
Identify opportunities to incorporate AI-driven capabilities into reporting, analytics, and decision support processes.
Partner with analytics teams to evaluate emerging technologies and improve the employee analytics experience.
Qualifications & Skills
Essential Qualifications
Experience working with organizational, workforce, HR, or people-related data.
Strong analytical and problem-solving skills with the ability to identify root causes behind business questions.
Advanced SQL skills with experience querying, analyzing, troubleshooting, and optimizing large datasets.
Strong understanding of data modeling concepts, including dimensional modeling, relationships, keys, hierarchies, and analytical data structures.
Proven ability to improve data quality, data integrity, and reporting accuracy across multiple systems and data sources.
Advanced Excel experience including Pivot Tables, XLOOKUP/VLOOKUP, formulas, conditional formatting, charts, and data analysis.
Ability to communicate complex analytical findings to non-technical audiences.
Experience building scalable reporting solutions, dashboards, and self-service analytics capabilities.
Strong collaboration skills and ability to work effectively across global teams and multiple time zones.
Ability to work within data governance, privacy, and compliance frameworks.
Flexible, proactive, and able to adapt to changing business priorities.
Excellent verbal and written communication skills.
Preferred Qualifications
Experience with HRIS platforms, preferably Workday.
Experience managing and analyzing structured and unstructured data using SQL, Python, R, or similar technologies.
Experience with BI and visualization tools such as Tableau, Power BI, Domo, or similar platforms.
Familiarity with ETL and data integration tools such as Alteryx, Informatica, or similar technologies.
Exposure to Generative AI technologies and AI-powered analytics solutions.
Experience designing analytical datasets, semantic layers, feature stores, or enterprise reporting models.
Understanding of data governance, metadata management, and enterprise data quality frameworks.
Experience influencing stakeholders and driving adoption across large, matrixed organizations.
Knowledge of workforce planning, talent analytics, organizational effectiveness, or employee experience analytics.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must abide by Mastercard security policies, ensure data confidentiality and integrity, report security breaches, and complete periodic mandatory security trainings.
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