Assoc Director Data Analytics

Uniti

1d•Onsite

About The Position

This individual will work cross-functionally across Product, Marketing, Base Management, and Finance to build dashboards and deliver insights that reduce churn and increase ARPU across our consumer organization. They will define and standardize key metrics, translate business questions into analysis, and communicate clear, actionable recommendations to product owners and senior stakeholders. The role will also help identify growth and retention opportunities through experimentation, customer segmentation, and funnel/cohort analysis, ensuring teams can consistently measure impact and make data-informed decisions.

Requirements

5+ years of experience in data analytics (consumer subscription/retention analytics a plus)
Advanced SQL skills and experience working with large, complex datasets
Strong Tableau skills (building scalable dashboards and self-serve reporting)

Responsibilities

Build and maintain executive-ready dashboards (Tableau) to monitor acquisition, engagement, retention, churn, and ARPU performance.
Partner with Product, Marketing, Base Management, and Finance to define KPIs/metric definitions and create a single source of truth for reporting.
Churn and retention analytics (cohort, funnel, and lifecycle analysis) to identify drivers, quantify impact, and prioritize initiatives.
Develop customer segments and behavioral profiles to tailor retention and monetization strategies and improve campaign/product targeting.
Design measurement plans for experiments and feature launches; evaluate lift/ROI and recommend next actions based on statistically sound analysis.
Build and maintain models (e.g., propensity, forecasting, scenario analysis) to understand ARPU drivers and predict retention and revenue outcomes.
Synthesize analysis into clear narratives and recommendations for leadership, including ongoing readouts on churn, ARPU, and initiative impact.
Improve data quality and usability by partnering with Data Engineering on instrumentation, data validation, and scalable dataset design.