Manager, Customer Analytics

Acrisure•Oklahoma City, OK

1d•Onsite

About The Position

We are seeking a Manager of Data Analytics to enhance our customer insights function within a fast-growing SaaS payroll company. This role will be responsible for transforming data into actionable insights to drive improvement opportunities, improve customer retention, and drive upsell revenue. The ideal candidate combines strong technical expertise (SQL, data modeling, BI tools) with a deep understanding of SaaS metrics and customer lifecycle dynamics. This leader will build predictive models, define customer health scoring, and partner cross-functionally to drive measurable business impact. This role sits at the center of our growth strategy. By identifying why customers leave—and enabling the business to act early—you will directly impact retention, expansion, and long-term revenue.

Requirements

8+ years in data analytics, business intelligence, or data science roles (preferably in SaaS)
Advanced SQL skills (non-negotiable; ability to work with large, complex datasets)
Hands-on experience building predictive models (churn, propensity, or customer scoring)
Strong experience with BI tools, especially Power BI
Experience integrating and analyzing data from systems like Salesforce, Genesys, and Pendo
Deep understanding of SaaS metrics (churn, customer count retention, GRR, NRR, LTV)
Strong analytical thinking and ability to connect data to business outcomes

Nice To Haves

Experience in payroll, HR tech, or SMB-focused SaaS businesses
Experience building customer health scoring frameworks from scratch
Background working closely with Customer Success or CX organizations
Familiarity with Python or R for statistical modeling and machine learning
Experience with experimentation (A/B testing) and causal inference

Responsibilities

Identify and quantify key drivers of customer churn across segments
Build and maintain churn prediction models using behavioral, transactional, and engagement data
Conduct cohort and churned vs. retained analysis to uncover retention patterns and risk signals
Translate insights into clear, actionable recommendations for Customer Success, Product, and Sales teams
Design and operationalize a scalable customer health scoring framework
Define leading indicators of customer risk and expansion opportunity
Partner with Customer Experience and Success and Operations teams to embed health scores into daily workflows
Integrate and model data across core systems: Salesforce, Genesys, Pendo, Qualtrics and Power BI
Build scalable data models to support self-service analytics and reporting
Ensure data accuracy, consistency, and governance across systems
Develop executive-level dashboards that track churn, retention, LTV, and customer health
Move beyond descriptive reporting to diagnostic and predictive insights
Standardize KPI definitions across the organization
Partner with Operations, Customer Experience/Success, Product, Sales, and Finance to align on metrics and insights
Influence strategy through data storytelling and business cases
Act as a translator between technical teams and business stakeholders