Data Scientist/ Analytics

AgreeYa Solutions • Colorado Springs, CO

2d

About The Position

AgreeYa is seeking a Data Scientist/ Analytics professional with experience in Looker, LookML, predictive modeling, and visualization. The role focuses on improving performance, predictability, and customer retention by using analytics to mitigate churn and maximize customer lifetime value. The successful candidate will develop solutions to complex attrition and retention problems, establish methods and evaluation criteria, and build intelligent automated workflows for churn reduction. The position also requires communicating technical risks, agentic logic, and churn analytics to nontechnical audiences and sharing knowledge with peers.

The role involves customer-lifecycle and attrition analysis, predictive modeling, and the development of interactive dashboards to track retention metrics, churn drivers, and cohort behavior. Preferred capabilities include agentic workflow development, enterprise semantic-layer design, statistical analysis of churn, and analytic storytelling for business partners.

AgreeYa is a global systems integrator established in 1999, headquartered in Folsom, California, and employing more than 1,800 professionals across its offices. The company serves more than 550 organizations across multiple industries. AgreeYa is an equal opportunity employer.

Requirements

• Bachelor’s degree or four or more years of work experience.
• Five years of relevant retail data domain experience, with emphasis on customer behavior, retention, and churn metrics.
• Experience in data management, analysis, and visualization focused on customer lifecycles and attrition patterns.
• Experience with Looker, specifically semantic-layer building using LookML, or a similar visual analysis tool.
• Experience with optimization, analytics, large data sets, project management, and developing visually compelling interactive dashboards.
• Experience as a data scientist, analyst, or statistical modeler specializing in predictive modeling, such as propensity-to-churn, risk scoring, or customer lifetime value modeling.

Nice To Haves

• Master’s degree in a quantitative discipline such as Mathematics, Statistics, Financial Economics/Econometrics, Engineering, Computer Science, or Operations Research.
• Hands-on experience in agentic development using AGK or similar agentic AI frameworks to build autonomous workflows, proactive customer intervention triggers, or automated churn-mitigation logic.
• Track record architecting, scaling, and maintaining LookML semantic layers to standardize retention, engagement, and customer health metrics across an enterprise.
• Ability and interest in communicating analytic findings and churn-mitigation insights to all levels, including reviewing model outputs and creating PowerPoint presentations and storyboards for business partners.
• Knowledge of retail channel metrics, customer retention dynamics, and data domain principles.
• Experience applying visual science and dashboard design principles to customer journeys, retention funnels, and churn rates.
• Experience applying statistical methods such as survival analysis, logistic regression, and time-to-event modeling to business problems involving customer churn.
• Knowledge of third-party analytic tools.
• Experience with Google Cloud Platform (GCP).
• Experience with Python, SQL, or R for churn modeling, feature engineering, and data-pipeline extraction.
• Experience with machine-learning algorithms and tools for predictive churn analysis, such as classification models, decision trees, and gradient boosting.

Responsibilities

• Develop solutions to complex customer attrition and retention problems.
• Build methods, evaluation criteria, and intelligent automated workflows to deliver churn-reduction solutions.
• Analyze customer lifecycles, customer behavior, retention, and attrition patterns.
• Develop predictive models, including propensity-to-churn, risk scoring, or customer lifetime value models.
• Build and optimize Looker/LookML semantic layers or similar visual analysis capabilities.
• Develop interactive dashboards to track retention metrics, churn drivers, and cohort behavior.
• Communicate technical risks, agentic logic, analytics findings, and churn-mitigation insights to nontechnical audiences and business partners.
• Share analytic knowledge with peers.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level