Director, Enterprise Performance Analytics

Upbound Group•Plano, TX

1d•Onsite

About The Position

The Director, Enterprise Performance Analytics (Growth) leads the strategy and execution of advanced analytics that drive enterprise growth, performance optimization, and data-informed decisioning. This role is accountable for delivering deep, full-funnel analytics across the customer lifecycle; from acquisition through servicing and collections to identify risks, uncover opportunities, and translate insights into measurable business impact. The Director partners closely with Growth product pod teams to embed analytics into product development, marketing, and customer experience initiatives. This includes designing and operationalizing measurement frameworks that quantify the incremental impact of product features, experiences, and innovations on conversion, retention, and lifetime value. This role serves as the analytical engine of the Growth organization connecting enterprise performance visibility with actionable insights that directly influence strategy, prioritization, and execution.

Requirements

10–15+ years in analytics, business analytics, product analytics, or customer analytics
5+ years leading high-performing analytics teams in a growth, product, or enterprise environment
Proven ability to influence senior leaders and drive measurable business outcomes
Deep expertise in full-funnel analytics across the customer lifecycle (acquisition through retention and collections)
Strong experience in cohort analysis, funnel decomposition, segmentation, and unit economics
Ability to diagnose performance drivers, identify risks, and quantify growth opportunities
Proven ability to connect operational metrics to financial outcomes (revenue, margin, LTV, ROI)
Strong experience designing and implementing measurement frameworks for product features and customer experience initiatives
Deep expertise in experimentation (A/B testing, holdouts, quasi-experimental methods) and causal inference
Ability to quantify incremental impact of product, marketing, and operational changes
Experience embedding analytics within cross-functional product or growth teams
Experience building forecasting models, scenario analysis, and predictive analytics to support planning and investment decisions
Ability to translate complex analyses into clear, actionable recommendations for business leaders
Strong orientation toward forward-looking insights and decision enablement
Proficiency in SQL and Python or R; experience with modern cloud data platforms (e.g., Snowflake, Databricks)
Familiarity with BI tools (Power BI, Tableau, Sigma) and scalable analytics environments
Strong understanding of data modeling, data quality, and governance principles
Experience building scalable analytics processes and repeatable frameworks for insight generation and experimentation
Strong focus on data quality, consistency, and reliability of analytical outputs
Ability to balance enterprise standardization with agility at the product or team level

Nice To Haves

Experience in Retail, Financial Services, FinTech, or multi-brand consumer environments
Experience working within product-led or growth-focused operating models

Responsibilities

Lead end-to-end analysis of the customer lifecycle (acquisition → onboarding → conversion → servicing → retention → collections) to identify performance drivers, bottlenecks, and opportunities
Diagnose conversion leakage, retention risks, and margin dynamics using cohort analysis, funnel decomposition, behavioral segmentation, etc.
Quantify drivers of growth, customer lifetime value (LTV), and unit economics across channels and products
Translate analytical findings into clear, prioritized actions that drive measurable business outcomes
Define and evolve enterprise KPI frameworks aligned to Growth strategy, financial goals, and operational levers
Establish standardized metric definitions while enabling deeper diagnostic layers for advanced analytics
Ensure consistency in performance measurement across product pods, brands, and channels
Connect operational metrics to financial outcomes, enabling true performance accountability
Embed analytics leaders within Growth product pods (e.g., acquisition, onboarding, servicing, retention)
Design and implement measurement frameworks to quantify the incremental impact of product features, customer experience enhancements, and innovations
Partner with Product and Marketing teams to support experimentation creating and implementing test-and-learn frameworks and causal inference approaches)
Ensure all major initiatives have clear success metrics, measurement plans, and post-launch impact evaluation
Drive a culture of evidence-based prioritization and continuous optimization
Deliver forward-looking insights that inform product roadmaps, marketing investments, and operational strategies
Proactively identify emerging risks and opportunities through trend analysis, predictive signals, and scenario modeling
Support strategic planning, forecasting, and investment decisions with robust analytical models
Serve as a trusted advisor to Growth leadership on performance optimization and trade-off decisions
Deliver concise, insight-driven executive dashboards and scorecards focused on key performance drivers
Ensure reporting highlights actionable insights—not just metrics—enabling faster and better decisions
Provide clear visibility into growth performance, initiative impact, and ROI across brands (Rent-A-Center, Acima, Brigit)
Standardize critical reporting while minimizing low-value or redundant outputs
Build scalable analytics capabilities that support both enterprise-level insights and product pod-level agility
Ensure high data quality, integrity, and governance across all analytical outputs
Establish repeatable processes for performance analysis, experimentation readouts, and insight delivery
Continuously improve speed, sophistication, and business impact of analytics