Managing Consultant Synthetic Data Expert

Role Overview: As a Managing Consultant Synthetic Data Expert (L6) at Mastercard, you will be responsible for developing and applying synthetic data approaches within primary quantitative market research. Your role involves managing quantitative research execution across fieldwork, scripting, data quality, and analysis for global research projects. 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 role does not involve people management or general project delivery. Key Responsibilities: - 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 low incidence or hard to reach populations, early testing of questionnaires or analysis plans, scenario modeling, and analytical stress testing, and data augmentation for exploratory analysis. - Primary Research & Methodological Integration - Work with ARC quantitative researchers to understand questionnaire design, survey logic, sampling approaches, weighting, and 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 - Apply advanced statistical, probabilistic, or ML based techniques as appropriate - Work with complex, multi-market, and weighted survey datasets - Support proof of concepts and pilots related to synthetic data and advanced modeling. Qualifications & Skills: Core Experience: - 58 years of experience in quantitative research, advanced analytics, or data science with meaningful exposure to survey-based primary research - Strong understanding of primary market research data structures, including variables, derived metrics, weighting, and fieldwork artifacts. Synthetic Data & Technical Skills: - Hands-on experience with synthetic data generation, simulation, or advanced modeling techniques - Strong proficiency in statistical or analytical programming (e.g., R, Python, or similar) - Solid grounding in statistics and probability, including model validation and performance assessment. Working Style & Collaboration: - Ability to explain complex technical concepts to nontechnical researchers and stakeholders - Comfortable operating as a specialist IC within cross-functional teams - Curious, rigorous, and pragmatic in evaluating trade-offs between innovation and research integrity - Strong documentation and communication skills. Additional Skills: - Experience working in research, consulting, or analytics-driven environments - Strong documentation and communication skills - Comfortable working as a specialist IC within cross-functional teams - Curious, rigorous, and thoughtful about methodological trade-offs. (Note: Omitted Corporate Security Responsibility as it was not directly related to the job role) Role Overview: As a Managing Consultant Synthetic Data Expert (L6) at Mastercard, you will be responsible for developing and applying synthetic data approaches within primary quantitative market research. Your role involves managing quantitative research execution across fieldwork, scripting, data quality, and analysis for global research projects. 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 role does not involve people management or general project delivery. Key Responsibilities: - 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 low incidence or hard to reach populations, early testing of questionnaires or analysis plans, scenario modeling, and analytical stress testing, and data augmentation for exploratory analysis. - Primary Research & Methodological Integration - Work with ARC quantitative researchers to understand questionna