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 (Winnipeg)
🏢 Rogers communications
📍 Winnipeg