Description

You will design, develop, and deploy machine learning models to predict customer churn risk.

This role is on-site.

Responsibilities

• Design and program methods to deploy predictive models like logistic regression and XGBoost.
• Engineer features from raw customer data and develop metrics for tracking engagement.
• Build automated processes to cleanse, integrate, and evaluate datasets for segmentation and training.
• Translate complex model outputs into actionable business insights for retention strategies.
• Optimize churn prediction models using metrics like AUC and lift.

Required Skills

• 5+ years of experience in data science or data engineering.
• Proficiency in Python and SQL.
• Strong understanding of data engineering concepts, including data lakes and columnar formats.
• Experience with ETL tools and BI tools.
• Demonstrated skill in statistical modeling for churn analysis and customer segmentation.
• Experience building, evaluating, and deploying machine learning models.
• Bachelor's Degree in Computer Science, Data Analytics, Engineering, or related field.

Key Skills

Education

Any Graduate