Data Scientist (Marketing Mix Modeling)

Our client, a leading global retail organization, is looking for a Data Scientist specializing in Marketing Mix Modeling to join their marketing analytics function. This role sits at the intersection of statistics, media strategy, and finance — translating rigorous econometric modeling into investment decisions that matter. About the Role You'll build, validate, and continuously improve marketing mix models that quantify the incremental impact of media and marketing investment across channels and markets. You'll also play a key role in evaluating and quality-governing modeling work delivered by external vendors and agency partners, acting as a credible technical counterpart to both marketing and finance stakeholders. What You'll DoBuild and validate econometric/MMM models — adstock transformations, diminishing returns curves, base vs. incremental decomposition, and ROI derivationApply advanced regression-based and panel/regional data modeling techniques, with rigorous diagnostics and out-of-sample validationDevelop production-grade modeling and simulation code in Python or R (not just exploratory notebook analysis)Incorporate Bayesian MMM approaches alongside classical regression methods where appropriateSense-check model outputs against real-world media behavior — short vs. long-term effects, channel synergy, and saturation dynamicsReview, challenge, and quality-govern modeling methodologies delivered by external vendors, agencies, or academic partnersAct as a bridge between Marketing and Finance, translating model outputs into clear, defensible investment recommendations What You'll Bring Must-Have:5+ years of hands-on experience building and validating Marketing Mix / econometric models in a commercial or agency settingAdvanced applied statistics/econometrics: regression-based modeling, panel/regional data structures, model diagnostics, holdout testing, and out-of-sample forecast validationStrong Python or R skills for production-grade modeling and simulationFamiliarity with Bayesian MMM approaches alongside classical regressionWorking knowledge of media channels and how they behave in a model — enough to sense-check results commercially, not just statistically Strong Plus:Experience in retail, FMCG, or another complex, multi-market organizationDemonstrated experience evaluating or challenging a third party's modeling methodology — you've been on the "receiving and questioning" side of a model, not only the "producing" sidePrior experience quality-governing an external modeling vendor's deliverablesExperience bridging Marketing and Finance stakeholders on investment questionsInterested candidates can apply directly or reach out to Arj Global for more details.