Director, Marketing Sciences & Customer Analytics

Upbound Group•Plano, TX

1d•Onsite

About The Position

The Director, Marketing Sciences & Customer Analytics (Growth) leads the strategy and execution of advanced marketing measurement, customer analytics, and personalization capabilities that drive profitable growth, marketing performance optimization, and data-informed decisioning. This role is accountable for quantifying and improving the effectiveness of marketing investments and customer experiences across the full customer lifecycle; from acquisition through engagement and retention to maximize conversion, lifetime value, and return on investment. The Director partners closely with Marketing, and Product Growth teams to embed marketing sciences and customer analytics into campaign strategy, customer journey design, and experience optimization. This includes designing and operationalizing measurement frameworks that quantify the incremental impact of media spend, targeting strategies, and personalization on customer acquisition, engagement, and retention. This role serves as the analytical engine for marketing performance and customer optimization, connecting marketing investment decisions and customer behavior with actionable insights that directly influence strategy, prioritization, and execution.

Requirements

10–15+ years in marketing analytics, marketing science, or customer analytics
5+ years leading analytics or marketing science teams
Proven ability to influence senior leaders and drive measurable growth outcomes
Deep expertise in Media Mix Modeling (MMM), attribution, and incrementality testing across omni-channel environments
Strong experience measuring performance across traditional (TV, radio, direct mail), digital (paid search, paid social, display, programmatic), and owned channels (CRM, email, app, web)
Ability to unify cross-channel measurement into a single view of marketing effectiveness and ROI
Strong understanding of full-funnel performance (acquisition through retention) across channels
Deep experience with experimentation frameworks (A/B testing, geo testing, holdouts, synthetic controls)
Strong grounding in causal inference methodologies to measure true incremental impact
Clear understanding of attribution limitations versus incrementality approaches
Experience navigating signal loss (e.g., cookie deprecation, iOS privacy changes) and evolving measurement strategies
Experience applying machine learning and AI to marketing use cases (propensity modeling, LTV, targeting, optimization)
Familiarity with AI-driven analytics, including predictive modeling, automated insights, and advanced MMM approaches
Exposure to privacy-safe measurement approaches (clean rooms, modeled conversions, probabilistic attribution)
Proficiency in SQL and Python or R; experience with cloud data platforms (e.g., Snowflake, Databricks, BigQuery)
Experience with digital analytics and MarTech ecosystem (e.g., GA4, ad platforms, CRM/CDP systems)
Familiarity with BI tools (Power BI, Tableau, Sigma) and scalable analytics environments
Strong experience in segmentation, personalization, and lifecycle analytics
Ability to diagnose funnel performance, conversion drivers, and retention dynamics
Proven ability to connect marketing and customer behavior to CAC, LTV, revenue, and margin outcomes

Nice To Haves

Experience in Retail, Financial Services, FinTech, or multi-brand consumer environments

Responsibilities

Lead measurement and optimization of marketing effectiveness and investment efficiency across digital and offline channels
Establish and scale Media Mix Modeling (MMM), attribution, and incrementality frameworks to quantify marketing impact
Design and govern test-and-learn experimentation frameworks to validate performance and continuously improve measurement models
Guide budget allocation and channel optimization using marginal return and incrementality insights
Drive analytic innovation using AI to decrease speed to insights and increase insights democratization
Partner with Marketing leadership to inform campaign strategy, investment prioritization, and in-flight optimization
Lead end-to-end analysis of customer journeys (acquisition → application → conversion → servicing → retention) to identify friction points and growth opportunities
Diagnose conversion leakage, abandonment drivers, and engagement gaps using funnel analysis, cohort analysis, and behavioral segmentation
Develop segmentation frameworks to enable targeted marketing and personalized customer experiences
Partner with Marketing and Product teams to design and operationalize journey interventions and experience improvements
Quantify the incremental impact of personalization, targeting, and customer experience enhancements
Design and implement incrementality testing frameworks across media, campaigns, and customer experiences
Establish rigorous experimentation standards, including test design, execution, and interpretation
Apply causal inference methodologies to isolate drivers of marketing and experience performance
Ensure all major marketing and customer experience initiatives have defined success metrics, measurement plans, and post-launch evaluation
Drive a culture of experimentation, evidence-based prioritization, and continuous optimization
Quantify drivers of customer acquisition, engagement, retention, and customer lifetime value (LTV)
Develop cohort-based and behavioral analytics to understand customer dynamics across segments and channels
Identify growth opportunities through deep analysis of marketing performance and customer behavior
Connect marketing and customer metrics to financial outcomes, including revenue, margin, and unit economics
Deliver forward-looking insights that inform marketing strategy, customer experience design, and growth investments
Proactively identify emerging risks and opportunities through trend analysis, predictive signals, and scenario modeling
Translate analytical findings into clear, prioritized actions that drive measurable business outcomes
Serve as a trusted advisor to Marketing and Growth leadership on performance optimization and investment decisions
Deliver concise, insight-driven dashboards and scorecards focused on key marketing and customer performance drivers
Ensure reporting highlights actionable insights (not just metrics) enabling faster and better decisions
Provide clear visibility into marketing ROI, CAC, conversion performance, and customer engagement across channels
Standardize critical reporting while minimizing low-value or redundant outputs
Build scalable marketing analytics and customer analytics capabilities that support enterprise-level insights and agile execution
Ensure high data quality, integrity, and consistency across all analytical outputs
Establish repeatable processes for marketing measurement, experimentation readouts, and insight delivery
Continuously improve speed, sophistication, and business impact of analytics