Project Detail

Contact Optimization for Improved Customer Interactions

Built predictive models and recommendation logic to improve customer interaction strategies while refactoring an existing application for better maintainability and performance.

Role
Data Scientist
Context
Telecommunications
Domain
AI Applications
Duration
15 months
Status
Finished

What changed

  1. Developed machine learning models to predict hotline demand and support more proactive customer engagement.

  2. Designed recommendation logic that helped call center agents identify more suitable customer tariffs, improving call efficiency and customer experience.

  3. Refactored the application codebase to improve maintainability, readability, and performance.

  4. Integrated model outputs into customer service workflows, enabling day-to-day operational use of predictions.

Technology

Python

6 technologies

pandas seaborn PySpark pytest Black Ruff

Machine Learning

2 technologies

Random Forest XGBoost

Databricks

5 technologies

Unity Catalog Databricks Clusters SQL Warehouses Databricks Asset Bundles MLflow

SQL

2 technologies

PL/SQL Spark SQL

Signals

machine-learning data-science customer-analytics application-development mlops