onsite
Lead Data Scientist - Propensity & Segmentation Telecom - Kodeva LLC
Data Scientist
Senior data scientist leading advanced propensity and segmentation projects in telecom, leveraging Python and machine learning to build and deploy supervised and unsupervised models that drive customer insights and revenue growth.
About the role
Key Responsibilities
- Design, develop, and deploy supervised and unsupervised machine learning models for customer propensity and segmentation in the telecom domain.
- Lead end‑to‑end data science projects, from data acquisition and feature engineering to model validation and production deployment.
- Collaborate with cross‑functional teams to translate business objectives into analytical solutions and actionable insights.
- Mentor and coach junior data scientists, fostering best practices in model development, testing, and documentation.
- Stay current with emerging techniques in class‑imbalance mitigation, feature selection, and probabilistic modeling to maintain competitive advantage.
Requirements
- 10+ years of professional experience as an applied data scientist in telecom or related industry.
- Deep expertise in machine learning theory and practical application, including propensity modeling and customer segmentation.
- Proficiency in Python, data manipulation libraries (pandas, NumPy), and ML frameworks (scikit‑learn, XGBoost, LightGBM).
- Strong analytical skills with a track record of delivering production‑ready models that impact business outcomes.
- Excellent communication skills and ability to translate complex technical concepts to non‑technical stakeholders.
Skills
pythonmachine learning