Build production machine learning models as a Manager, Data Scientist at Rogers in Toronto, using Python, Spark, Azure, and Databricks onsite. Own analytics influencing millions of customer interactions. This experienced individual contributor role spans the complete model development lifecycle. You will define business problems, engineer features, deploy models, and monitor performance. The work supports acquisition, retention, and lifecycle marketing through advanced analytics, experimentation, and predictive modeling.

Key Responsibilities
- Design, validate, deploy, and monitor production machine learning models
- Perform feature engineering, model selection, tuning, and evaluation
- Translate business objectives into analytical approaches and success metrics




- Collaborate with Data Engineering and MLOps on operationalization
- Explore Generative AI and large language models for business value

Requirements:
- Five to eight years in data science, machine learning, or applied AI
- Solid Python, SQL, and Spark programming skills
- Production experience developing and deploying machine learning models
- Knowledge of experimentation, statistical analysis, and predictive modeling
- Azure and Databricks experience strongly preferred Bring production modeling, stakeholder partnership, and advanced analytics expertise to Rogers as a Toronto-based Data Scientist Manager.

📌 Manager Data Scientist Machine Learning (Toronto)
🏢 Rogers communications
📍 Toronto