Director

Publicis Groupe Holdings B.V; Bengaluru; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

Publicis Groupe Holdings B.V. seeks an experienced Analytics leader to head Marketing Mix Modelling, MMM, and advanced analytics engagements for major brands. The role combines hands-on modelling with client leadership and team management across markets.

The ideal candidate will guide model architecture, ensure robust causal reasoning, and oversee governance of analytics outputs to support marketing investment decisions.

Qualifications

• 8-12+ years of experience in Analytics/Marketing Science/Econometrics/Data Science or Marketing Effectiveness.
• Strong hands-on experience in Marketing Mix Modelling (MMM).
• Proven experience owning large multi-brand/multi-market MMM programmes.
• Deep understanding of OLS/econometric and Bayesian MMM approaches.
• Strong knowledge of model architecture, causal inference, identifiability and multicollinearity.
• Hands-on Bayesian concepts including priors, posterior diagnostics, R-hat, ESS, divergences and posterior predictive checks.

Responsibilities

• Lead end-to-end Marketing Mix Modelling (MMM) and Marketing Effectiveness engagements across brands and markets.
• Provide technical leadership on model architecture and pooling/partial-pooling approaches.
• Review and challenge model specifications, transformations, priors, diagnostics, and ROI outputs.
• Ensure analytical outputs are supported by causal reasoning and statistical evidence.
• Identify and address endogeneity, reverse causality, confounding, multicollinearity, and identifiability issues.
• Lead Bayesian and frequentist/econometric modelling and manage uncertainty and diagnostics.

Skills

Analytics

MarketingScience

Econometrics

DataScience

MarketingEffectiveness

MarketingMixModelling

CausalReasoning

ModelGovernance

StakeholderManagement

TeamLeadership

Job description

Overview

AssociateDirector/Director-Analytics

Location:Bengaluru/Gurgaon

Experience:6-10+years

Function:Analytics/MarketingScience/Measurement

AbouttheRole

WearelookingforanexperiencedAnalyticsleadertoleadhigh-impactMarketingMixModelling(MMM),MarketingEffectiveness,EconometricsandAdvancedAnalyticsengagementsforleadingbrands.

Therolerequiresastrongcombinationofhands-onmodellingexpertise,causalreasoning,modelgovernance,clientleadershipandteammanagement.Theidealcandidateshouldbecomfortablechallenginganalyticalassumptions,reviewingmodelsbuiltbyteamsanddeterminingwhetherinsightsarerobustenoughtosupportbusinessandmarketinginvestmentdecisions.

KeyResponsibilities

• Leadend-to-endMarketingMixModelling(MMM)andMarketingEffectivenessengagementsacrossbrands,marketsandcategories.
• Providetechnicalleadershiponmodelarchitecture,includingdecisionsaroundseparate,pooled,hierarchicalandpartial-poolingapproaches.
• Reviewandchallengemodelspecifications,transformations,priors,diagnostics,contributionestimatesandROIoutputs.
• Ensureanalyticaloutputsaresupportedbysoundcausalreasoningandstatisticalevidence.
• Identifyandaddressissuesrelatedtoendogeneity,reversecausality,confounding,multicollinearityandidentifiability.
• LeadBayesianandfrequentist/econometricmodellingapproachesandensureappropriateuseofuncertaintyanddiagnostics.
• Evaluatemodelstabilitythroughsensitivityanalysis,holdouts,alternativespecifications,transformations,priorsandtimewindows.
• ReconcileMMMfindingswithgeoexperiments,incrementalitystudiesandothermeasurementapproaches.
• Governmarketingbudgetoptimizersandensurerecommendationsaresupportedbyrobustevidenceandappropriateconstraints.
• Distinguishbetweenpredictionqualityandattributionqualitywhenevaluatingmodels.
• Reviewandapprovemodelsdevelopedbyanalystsanddatascientistsbeforeclientdelivery.
• Leadandmentoranalytics/datascienceteamsworkingacrossmultipleprojectsandmarkets.
• Partnerwithseniorclientstakeholderstotranslatecomplexanalyticalfindingsintoclearbusinessandinvestmentrecommendations.
• Challengeunreasonableclientexpectationsandcommunicatelimitationsofthedataandmethodologyeffectively.
• Contributetonewbusiness,pitchesanddevelopmentofanalyticssolutionsandmethodologies.

WhatWe’reLookingFor

• 8-12+yearsofexperienceinAnalytics,MarketingScience,Econometrics,DataScienceorMarketingEffectiveness.
• Stronghands-onexperienceinMarketingMixModelling(MMM).
• Provenexperienceowninglargemulti-brand/multi-marketMMMprogrammes.
• StrongunderstandingofbothOLS/econometricandBayesianMMMapproaches.
• Deepunderstandingofmodelarchitecture,causalinference,identifiabilityandmulticollinearity.
• Stronghands-onunderstandingofBayesianconceptsincludingpriors,posteriordiagnostics,R-hat,ESS,divergencesandposteriorpredictivechecks.
• Experiencewithadstock,saturation,responsecurvesandcontributionmodelling.
• Strongunderstandingofendogeneity,reversecausality,confoundersandmediators.
• ExperiencereconcilingMMMresultswithexperimentation/geotesting/incrementalitystudies.
• Experiencewithmodelstability,sensitivitytestingandmodelgovernance.
• Experiencereviewingandapprovingmodelsdevelopedbyotheranalysts/datascientists.
• Strongclient-facingandstakeholdermanagementexperience.
• Provenexperienceleadingandmentoringanalyticsteams.