About this role
Job Description About the Job: We are seeking a business-focused Data Scientist to use data science, advanced analytics, Machine Learning, and AI to generate insights, improve customer experience, optimize operations, and support strategic decision-making across business functions. The ideal candidate will combine strong technical skills with business understanding and the ability to work closely with business, product, data engineering, and technology teams.
Office Location: Toronto
Employment Type: Permanent
Role Type: New position ? current requirement
Work Arrangement: Hybrid (2 days in office per week)
Position Responsibilities:
Predictive Modeling & Forecasting: Design, train, and validate robust traditional machine learning models and advanced time-series forecasting algorithms (e.g., for demand planning, inventory optimization, and sales forecasting).
End-to-End GCP Deployment: Architect and productionize scalable predictive pipelines leveraging Google Cloud Platform (e.g., BigQuery, Vertex AI). Transition models from local/development environments to highly optimized, automated cloud deployments.
Data Wrangling & Processing: Ingest, organize, and manipulate billions of rows of data from dozens of disparate sources using highly efficient SQL and Python scripts to ensure data quality and model reliability.
Business Partnership & Insights: Act as a strategic bridge between technical and non-technical teams. Translate complex model outputs into actionable business strategies, presenting findings, test results, and performance analyses to senior management.
Mentorship & Leadership: Provide technical guidance, code reviews, and architectural support to junior data scientists and ML engineers, navigating complex real-world business problems on a case-by-case basis.
Continuous Innovation: Constantly upskill and remain fully updated with the evolving data and analytics community, integrating new traditional ML techniques and exploring emerging technologies.
Requirements
• 5+ years of applied industry experience in data science, statistical analysis, and machine learning.
• Ph.D. or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
• Deep expertise in traditional machine learning algorithms (regression, classification, clustering, tree-based models) and a strong specialization in forecasting techniques (e.g., ARIMA, Prophet, exponential smoothing). </spa