Data Scientist to Develop Predictive Customer Churn Models
Skills Required
Description
We are seeking a data scientist who can design and implement predictive churn models that provide actionable insights for our customer retention strategies.
The role requires someone who can take raw customer data, clean it, and extract features that truly capture the behavior patterns leading to churn.
Our primary goal is to identify customers at risk before they leave and create opportunities for proactive outreach campaigns.
We need expertise in working with large datasets, applying statistical models, and experimenting with machine learning techniques for accurate predictions.
The project involves not only building the models but also testing them using controlled experiments to ensure that the outcomes are reliable and meaningful.
Clear reporting is an essential part of this engagement. We expect results to be presented in a way that non-technical stakeholders can easily understand.
The ideal candidate should be comfortable using Python along with libraries such as Pandas and Scikit-learn for data manipulation and model development.
You will collaborate with teams across marketing and customer support to align churn predictions with business objectives.
It’s important that you understand how online customer engagement, including search and digital touchpoints, can influence churn rates.
Strong analytical thinking combined with practical business sense is highly valued for this role.