ARC Research Manager – Quantitative Research, Data Processing (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 Research, Data Processing (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 supports the visualization and communication of quantitative research findings for global projects. Role: As a Quantitative Research Manager – Data Processing, you will be responsible for managing and delivering data processing workstreams across quantitative research projects. You will work independently on defined components of projects and collaborate closely with ARC researchers, fieldwork teams, visualization teams, and external partners to ensure data accuracy, consistency, and readiness for analysis. Candidates for this position should have strong hands on experience with quantitative data processing and be comfortable taking ownership of data quality and delivery across multiple projects. Key responsibilities include: • Manage and execute key components of quantitative research projects across global and regional studies • Oversee quantitative fieldwork execution, including sampling, quotas, timelines, and coordination with research vendors • Monitor fieldwork progress and proactively manage risks related to incidence, quotas, timelines, or data quality • Conduct and review data quality checks during and post fieldwork, and resolve issues related to sample integrity or response quality • Support quantitative analysis and interpretation of survey data in collaboration with senior researchers • Translate data into clear findings and support the development of research outputs and materials • Coordinate closely with data processing and visualization teams to ensure smooth hand offs across project stages • Maintain clear documentation related to project execution, decisions, and learnings Qualifications & Skills: • 5–7 years’ experience at a research agency or in an in‑house research role supporting quantitative research data processing • Strong understanding of quantitative research data structures and processing workflows • Hands‑on experience with data processing and statistical tools (e.g., SPSS, Q, R, Excel, or similar) • Experience applying data quality checks and validation rules across large datasets • Ability to manage multiple datasets and processing workstreams simultaneously • Strong attention to detail and quality orientation • Comfortable working in fast‑paced, deadline‑driven environments • Experience supporting multi‑market or regional studies is strongly preferred All About You • Detail oriented and focused on delivering high quality, accurate data • Comfortable taking ownership of defined workstreams and delivering against timelines • Confident working with structured datasets and research tools • Collaborative and effective when wo ... (truncated, view full listing at source)