ARC Research Manager – Quantitative Market Research, Data Innovation (L7)

Our Purpose Mastercard powers economies and empowers people in 200 countries and territories worldwide. Together with our customers, we’re 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. Title and Summary ARC Research Manager – Quantitative Market Research, Data Innovation (L7) Overview The Advisors Research Center (ARC) is a global team of researchers within Mastercard that delivers high‑quality, end‑to‑end research in support of Mastercard’s Advisors and Consulting Services. ARC partners closely with consulting teams and internal stakeholders to design, execute, and deliver rigorous research that informs strategic decision‑making for clients across industries and markets. As part of ARC’s continued growth, Global Facilities India (GFI) supports global and regional ARC engagements by providing scalable, high‑quality quantitative research delivery. The GFI team works closely with ARC researchers and consultants to ensure consistency, speed, and quality across research execution and outputs. This role sits within the ARC Quant Research capability in GFI and plays a key role in managing quantitative research execution across fieldwork, scripting, data quality, and analysis for global research projects. Role: As a Research Manager – Quantitative Research, Data Innovation (L7), you will manage end‑to‑end quantitative research workstreams while also driving innovation in research delivery through the thoughtful use of AI, automation, and advanced analytics. This is not a pure data science role. The role is designed for a market researcher first, who understands how studies are designed, fielded, analyzed, and reported—and who can apply AI tools and techniques to improve efficiency, quality, and insight generation across that lifecycle. Key responsibilities include: Quantitative Research Delivery • Manage and execute end‑to‑end quantitative research workstreams across global and regional studies • Lead fieldwork execution, including sample management, quality checks, and coordination with panels • Own data analysis and insight development, ensuring outputs are accurate, relevant, and decision‑focused • Translate quantitative findings into clear narratives and implications for clients Data & AI‑Driven Innovation • Apply AI and automation tools to improve research workflows (e.g., faster data cleaning, quality checks, analysis, or visualization) • Experiment with new analytical approaches within primary research (e.g., automated coding, advanced statistical techniques, model‑assisted interpretation) • Identify opportunities to standardise, streamline, or automate repetitive research processes • Work closely with data processing, visualization, and advanced analytics teams to pilot and scale new approaches Technical & Analytical Oversight • Review and validate survey scripts (logic, flows, edge cases) in collaboration with scripting teams • Ensure data quality and integrity across datasets before analysis and reporting • Use analytical tools (e.g., SPSS, R, DisplayR, Q, or similar) to run structured analyses beyond basic crosstabs • Support the development of reusable analysis frameworks, templates, and standards Collaboration & Ways of Working • Partner with ARC researchers, consultants, and GFI counterparts across regions • Contribute to best practices, documentation, and knowledge sharing within the team • Proactively flag risks, data issues, or methodological concerns and recommend solutions Qualifications & Skills: Core Research Experience • 5–7 years of experience in primary quantitative market research, ideally in a research agency or consulting led environment • Strong understanding of end to end survey re ... (truncated, view full listing at source)