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 Do
- Build and validate econometric/MMM models — adstock transformations, diminishing returns curves, base vs. incremental decomposition, and ROI derivation
- Apply advanced regression-based and panel/regional data modeling techniques, with rigorous diagnostics and out-of-sample validation
- Develop production-grade modeling and simulation code in Python or R (not just exploratory notebook analysis)
- Incorporate Bayesian MMM approaches alongside classical regression methods where appropriate
- Sense-check model outputs against real-world media behavior — short vs. long-term effects, channel synergy, and saturation dynamics
- Review, challenge, and quality-govern modeling methodologies delivered by external vendors, agencies, or academic partners
- Act 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 setting
- Advanced applied statistics/econometrics: regression-based modeling, panel/regional data structures, model diagnostics, holdout testing, and out-of-sample forecast validation
- Strong Python or R skills for production-grade modeling and simulation
- Familiarity with Bayesian MMM approaches alongside classical regression
- Working 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 organization
- Demonstrated 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" side
- Prior experience quality-governing an external modeling vendor's deliverables
- Experience bridging Marketing and Finance stakeholders on investment questions
- Interested candidates can apply directly or reach out to Arj Global for more details.