Our Purpose
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Title and Summary
ARC Quantitative Research Manager – Data Processing & Analytics
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.
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 & Analytics, you will own data processing and analytical workstreams across quantitative research studies. You will be responsible for transforming raw survey data into clean, structured, and analysis‑ready datasets, while also applying statistical techniques to support interpretation and insight development in partnership with ARC researchers.
Candidates for this position should be comfortable taking ownership of data integrity, applying analytical judgment, and proactively identifying patterns, risks, and opportunities within complex datasets.
Key responsibilities include:
• Own and deliver quantitative data processing and modelling workstreams across global and regional studies
o Advise on data structure, weighting approaches, and analytical feasibility for downstream research needs
o Sense‑check analytical outputs, identify patterns or anomalies, and proactively flag implications or considerations to researchers
• Perform data preparation (e.g., cleaning, validation, transformation) survey datasets for analysis
o Apply structured QC frameworks, logic checks, and consistency rules to ensure data integrity
o Review in‑field and post‑field data to identify outliers, inconsistencies, and logic issues, and troubleshoot in collaboration with fieldwork and scripting teams
• Apply standard statistics, such as significance testing, weighting, and normalization
• Ability to design and conduct advanced analysis based on the project request (supported by suitable software), including but not limited to driver analysis, CA (correspondence analysis), PCA (principal component analysis), TURF, MaxDiff, Conjoint, Clustering (e.g., K-means, Latent Class) is a plus
• Deliver structured outputs based on the DP spec, including cross‑tabulations (weighted and unweighted), coding, and analysis‑ready datasets
• Deliver client-ready advanced analysis output (e.g., simulator, tagging tools, spreadsheets)
• Partner with ARC researchers to shape analytical approaches and support insight development
• Maintain clear documentation, codebooks, and processing notes for each project
• Provide guidance and informal mentorship to junior data processing team members
• Contribute to continuous improvement of data processing and analytical standards, tools, and ways of working
Qualifications & Skills:
• 5–10 years’ experience in a market research agency or in‑house role supporting quantitative research data processing and analysis
• Bachelor’s degree in Statistics, Mathematics, Economics, Engineering, Computer Science, Data Science, or a related field, or equivalent practical experience
• Strong hands‑on experience with data processing and statistical tools (e.g., SPSS, Q, R, and data visualization tools like DisplayR, or similar)
• Experience creating cross‑tabulations and structured analytical outputs
• Knowledge of quantitative analytical techniques such as regression, MaxDiff, and driver analysis is a plus
• Strong understanding of quantitative research data structures and processing workflows
• Ability to interpret data outputs and translate findings into clear observations for research teams
• High attention to detail, strong analytical thinking, and problem‑solving skills
• 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 working across global, cross functional teams
• Proactive in identifying data issues and proposing solutions
• Able to balance speed with rigor and quality
• Thrive in a fast paced, dynamic research environment
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’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
