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Tier-1 brand, mid-level data role, metro location, and popular skillset increase applicant competition.
Core data science skills are transferable, but MMM and marketing domain expertise increase industry specificity.
Explicit 3+ years overall, 2+ years MMM, advanced degree and strong Python/MMM requirements.
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Develop and maintain Marketing Mix Modelling (MMM) and other marketing analytics models to provide actionable business insights.
Collaborate closely with global marketing analytics lead, business stakeholders, data engineers, and subject matter experts to design and execute analytics projects.
Manage end-to-end model development including data collection, validation, exploratory analysis, modeling for short-term and long-term marketing impact, and optimization.
3+ years of experience in Data Science, Analytics, or Machine Learning with at least 2 years hands-on experience specifically in Marketing Mix Modelling (MMM).
Advanced degree required in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, Operations Research, or Computer Science.
Strong coding skills in Python with ability to develop production-level code adhering to best practices.
Industry experience in Oil & Gas, Downstream, Mobility, Retail, CPG, or FMCG is desirable but not mandatory.
Experience working in cross-functional teams involving marketing, sales, IT, and data engineering for complex analytics project delivery.
Deep expertise in marketing analytics domain including familiarity with concepts like adstock, saturation, channel attribution, campaign testing, and pricing analytics.
Practical knowledge of advanced machine learning and optimization techniques applicable to MMM and media budget optimization problems, with exposure to open-source MMM libraries (e.g., PyMC, Robyn).