Senior Data Scientist–Market Mix Modeling

We are looking for a Senior Data Scientist – MMX to join our growing team. In this role, you will lead and contribute to Marketing Mix Modeling (MMM) and advanced analytics engagements. You will work closely with business stakeholders, translate business challenges into analytical problems, build statistical and machine learning models, and deliver actionable insights to optimize marketing investments and ROI. • Lead end-to-end development of Marketing Mix Models (MMM), from data preparation to model building, validation, and business recommendations. • Design and implement econometric/statistical models (regression, Bayesian methods, time series, hierarchical modeling) to measure and forecast marketing ROI. • Collaborate with clients and internal stakeholders to understand business objectives, translate them into analytical frameworks, and present insights with clarity. • Mentor and guide junior team members in MMM techniques, coding best practices, and business storytelling. • Drive automation and scalability in modeling pipelines and reporting dashboards. • Explore and apply emerging methods (e.g., causal inference, machine learning) to enhance traditional MMM approaches. • Communicate findings effectively through visualizations, presentations, and business-focused storytelling. Required Skills and Experience • 4–8 years of experience in advanced analytics, with a strong focus on Marketing Mix Modeling. • Proven experience leading MMM projects for global clients across industries (CPG, Retail, BFSI, Tech, etc.). • Strong statistical/econometric modeling skills (e.g., regression, time series, Bayesian methods). • Proficiency in programming languages such as Python and/or R. • Hands-on experience with SQL for data extraction and transformation. • Strong problem-solving skills and ability to work with large, complex datasets. • Excellent client-facing skills, with experience in consulting and presenting insights to senior business stakeholders. • Ability to manage multiple projects in a fast-paced, dynamic environment.