Managing Consultant – Synthetic Data Expert (Primary Market Research) (L6)

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 Managing Consultant – Synthetic Data Expert (Primary Market Research) (L6) 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 Managing Consultant – Synthetic Data Expert (L6), you will be responsible for developing and applying synthetic data approaches within primary quantitative market research. This role is designed for a technically strong specialist who deeply understands survey data, respondent behavior, and statistical validity, and can design synthetic data solutions that augment—rather than replace—real-world primary data. This role deliberately combines: • Strong understanding of primary quantitative research (survey design, data structures, weighting, analysis), and • Deep technical capability in synthetic data, simulation, and advanced modeling You will work closely with quantitative researchers, data processing teams, and advanced analytics colleagues to ensure synthetic data is applied responsibly, transparently, and only where it adds real value. This is not a people management or general project delivery role. Key responsibilities include: Synthetic Data Design & Application • Design and generate synthetic survey datasets based on real primary research data • Develop models that preserve key statistical properties, distributions, and variable relationships • Apply synthetic data techniques for defined research use cases, such as: o Low incidence or hard to reach populations o Early testing of questionnaires or analysis plans o Scenario modeling and analytical stress testing o Data augmentation for exploratory analysis ________________________________________ Primary Research & Methodological Integration • Work with ARC quantitative researchers to understand: o Questionnaire design and survey logic o Sampling approaches and weighting o Analysis objectives and constraints • Ensure synthetic outputs remain methodologically aligned with primary research principles • Clearly articulate where synthetic data can and cannot be used within survey research ________________________________________ Validation, Governance & Risk • Develop and apply validation frameworks to compare synthetic data with real respondent data • Assess bias, variance, and limitation risks associated with synthetic generation • Document methodologies, assumptions, and caveats clearly • Support the development of governance standards for synthetic data usage in ARC ________________________________________ Technical Execution & Advanced Analytics • Build reproducible synthetic data pipelines using statistical or analytical programming tools • ... (truncated, view full listing at source)