Job DescriptionAbout 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).
- Advanced, production-level programming skills in Python (Pandas, Scikit-Learn, Statsmodels) and highly complex SQL for large-scale data manipulation.
- Strong, hands-on proficiency in the Google Cloud Platform ecosystem. Experience building, training, and deploying models using Vertex AI, BigQuery, and Google Cloud Storage.
- Exceptional ability to distill complex data into meaningful business insights. Effective written and verbal communication skills are mandatory for cross-functional collaboration.
Preferred Qualifications:- Knowledge or hands-on experience with Deep Learningarchitectures and Generative AI (e.g., LLMs, building Retrieval-AugmentedGeneration (RAG) pipelines).
- Previous experience applying data sciencewithin the retail sector (e.g., supply chain forecasting, pricingoptimization, customer lifetime value).
- Familiarity with containerizing workloads (Docker)and using orchestration tools (like Google Cloud Composer / ApacheAirflow) to schedule and trigger complex ML training pipelines.
- Familiarity with tracking and documentation toolssuch as JIRA and Confluence.
BenefitsSalary Range: CAD $100,000 - $115,000/year
The final compensation offered will depend on local market conditions and geographic location, as well as job-related factors such as the candidate's knowledge, skills, qualifications, relevant experience, and education/training. Compensation may also include additional components such as benefits, and/or other incentives, where applicable. In accordance with new employment standards requirements, we retain copies of this job posting and applicant information for three (3) years after the posting is removed. We do not use AI technology; all applications are also reviewed by our recruitment team.
