Job Title: Data Scientist/ AnalyticsLocations: Colorado Springs CO / Basking Ridge NJ / Temple Terrace FL/ Lake Mary FL/ Irving TX / Alpharetta GAJob SummaryAgreeYa is global Integrator and seeking for a Data Scientist/ Analytics who has strong experience in Looker, LookML, Predictive modeling and visualization etc.
We are looking for an eye towards improving performance, predictability, and customer retention, you thrive on the science of analytics to mitigate churn and maximize customer lifetime value. Developing resolutions to complex attrition and retention problems using your sharp judgment to build methods, evaluation criteria, and intelligent, automated workflows allows you to deliver high-impact churn-reduction solutions. You're able to communicate complex technical risk, agentic logic, and churn analytics to non-technical audiences, and you take pride in your ability to share your considerable knowledge with your peers.
Must have:
- Bachelor's degree or four or more years of work experience.
- Five years of relevant retail data domain experience, with a focused emphasis on customer behavior, retention, and churn metrics.
- Experience in data management, analysis, and visualization centered on customer lifecycles and attrition patterns.
- Experience in Looker-specifically with semantic layer building using LookML-or a similar visual analysis tool, optimization, analytics, large data sets, project management, and developing visually compelling interactive dashboards to track retention metrics, churn drivers, and cohort behavior.
- Experience as a data scientist, analyst, or statistical modeler specializing in predictive modeling (e.g., propensity-to-churn, risk scoring, or customer lifetime value modeling).
Even better if you have one or more of the following: - A 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.
- Proven track record architecting, scaling, and maintaining robust semantic layers using LookML to standardize retention, engagement, and customer health metrics across the enterprise.
- A passion for educating and communicating analytic findings and churn mitigation insights with integrity to all levels: from reviewing raw model outputs with colleagues to creating PowerPoint presentations and storyboards that captivate and succinctly convey complex attrition trends and strategic retention plans to business partners.
- Demonstrated knowledge of Retail Channel metrics, customer retention dynamics, and data domain principles.
- Experience in visual science and dashboard design principles applied to tracking customer journeys, retention funnels, and churn rates.
- Experience in applying statistical ideas and methods (e.g., survival analysis, logistic regression, time-to-event modeling) to data sets to solve business problems related to customer churn. Knowledge of third-party analytic tools.
- Experience with Google Cloud Platform (GCP).
- Experience with programming languages like Python, SQL, or R for churn modeling, feature engineering, and data pipeline extraction.
- Experience with Machine Learning algorithms and tools applied to predictive churn analysis (e.g., classification models, decision trees, gradient boosting).
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