Job Description

Overview:

The Data Scientist designs, develops, and deploys predictive models and advanced analytics solutions to drive business insights and operational improvements. This role collaborates closely with data engineers, architects, and business stakeholders to translate requirements into actionable models and supports integration of AI/ML into BI platforms.
Responsibilities:

Model Development & Delivery

Build and iterate models for churn prediction, network performance, and other business-critical use cases. Conduct feature engineering, model training, validation, and deployment. Collaboration & Integration Work with data engineers and architects to ensure data readiness and seamless model integration. Support dashboarding and reporting initiatives in Tableau and other BI platforms. Innovation & Enablement Evaluate and implement natural language querying solutions. Document model development processes and results for governance and reproducibility. Continuous Improvement Monitor model performance, retrain as needed, and apply mitigation actions for drift and decay. Stay current with emerging ML techniques and tools.
Requirements:

Technical Expertise

3+ years in data science roles with hands-on experience in predictive modeling and analytics. Proficiency in Python, R, and ML frameworks (scikit-learn, TensorFlow, PyTorch). Experience with cloud data platforms (Snowflake, Azure ML) and BI tools (Tableau, Power BI). Collaboration & Communication Strong ability to translate business needs into technical solutions. Effective communicator across technical and non-technical teams. Tools & Technologies Familiarity with feature engineering, model validation, and deployment best practices. * Understanding of data governance and reproducibility standards.