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Tier-1 brand, mid-level generalist data role, metro location, and broad skillset increase competition.
Marketing analytics skills transfer across industries but domain-specific MMM experience raises specialization moderately.
Explicit 3+ years, 2+ years MMM, advanced degree and strong Python/MMM requirements make filters strict.
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Develop and maintain advanced marketing analytics models, specifically Marketing Mix Models (MMM), to deliver actionable insights for business marketing decisions.
Collaborate closely with marketing analytics leads, business stakeholders, and cross-functional teams to ensure models meet business needs and support analytics projects from design through execution.
Manage data collection, validation, and processing workflows in coordination with data engineers to support model development and deployment.
Minimum 3+ years experience in Data Science, Analytics, or Machine Learning, with at least 2+ years hands-on experience in Marketing Mix Modelling.
Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, Operations Research, or related quantitative field.
Strong Python coding skills with ability to develop production-level code following best practices.
Good knowledge of Marketing domain concepts including ATL/BTL marketing, adstock/carryover, saturation, and experience with marketing analytics use cases such as channel attribution, pricing analytics, campaign effectiveness testing.
Experience working with marketing analytics in industries like Oil & Gas, Downstream, Mobility, Retail, CPG, or FMCG, indicating domain fit for Shell's business units.
Comfortable handling end-to-end MMM development from data processing, exploratory analysis, to short and long-term impact modeling, and budget optimization problems.
Able to collaborate effectively across multiple stakeholders including business SMEs, data engineers, digital product owners, and analytics teams in a global organizational setting.