Job Title

The Senior Data Scientist is a hands-on builder and experienced delivery leader. This person takes models from concept through deployment to a recommendation a VP can act on Monday morning. They bring deep experience across customer economics, marketing measurement, audience development, forecasting, and enterprise strategy and can connect analytical work to merchandising priorities and broader economic context. They coach junior team members, elevate methodology, and raise the standard on what “delivered” means.Core Competency AreasCustomer Economics & Lifecycle AnalyticsLTV modeling, churn/retention analysis, segmentation, and reactivation strategiesTranslating customer-level outputs into segment P&L narratives and investment guidanceMarketing Measurement & AttributionIncrementality testing, media mix modeling, and multi-touch attributionCausal inference methods: matched markets, synthetic controls, DiD, Bayesian approachesAudience Building & SegmentationPredictive audiences, look-alike models, propensity scores, and behavioral segments for media and CRM activationClosing the loop between model outputs and in-market performanceForecasting & Business PlanningTime series and ML-based forecasting for demand, revenue, category performance, and budget planningSurfacing forecast risks and opportunities as forward-looking business recommendationsEconomic & Financial InterpretationInterpreting macroeconomic signals (e.g., housing starts, consumer confidence, commodity pricing, interest rates) to contextualize business performancePartnering with Finance and executive leadership to translate external conditions into demand and investment implicationsEnterprise Strategy AnalyticsConnecting analytical work to corporate planning priorities and executive decision-makingLeading ad-hoc strategic analyses: market sizing, competitive positioning, growth scenario modelingMerchandising AnalyticsApplying data science to inventory optimization, space planning, and assortment strategyPartnering with Merchandising leadership to translate model outputs into actionable planning inputsExperimentation & Test DesignTranslating business questions into testable hypotheses with proper experimental design and power analysisA/B and multivariate test measurement with clear communication of resultsWhat This Person Does Day to DayBuilds and deploys models in Python and SQLDelivers finished insight packages: context, implications, and recommended actionsCoaches team members on methodology, interpretation, and framing the “so what”Drives quality through code reviews and shared documentationIntegrates outputs into Power BI and Microsoft Fabric pipelinesEngages directly with senior stakeholders across Marketing, Finance, Merchandising, and StrategyExperience5–7+ years in data science, analytics, or marketing measurement with progressive delivery ownership in enterprise environmentsStrong fundamentals in customer economics, measurement/attribution, and forecasting—hands-on delivery, not just awarenessDemonstrated ability to connect analytical work to enterprise strategy and interpret economic/financial dataExperience with merchandising analytics (inventory, space planning, assortment) preferredExpert in Python and SQL; comfortable with production-grade code, version control, and pipeline automationTrack record of delivering results to senior leadership: building the model, telling the story, making the recommendationExperience mentoring team members on technical methodology and business communicationRetail, e-commerce, or DTC industry experience preferredMaster’s degree in a quantitative field preferred