Data Scientist developing machine - learning models for The Athletic’s sports media platform. Optimizing subscriptions, workflows, experiments, and personalized article recommendations.
About the role
- Data Scientist role at Coke Canada Bottling focusing on advanced analytics and data-driven initiatives. Collaborating across teams to solve complex business challenges through machine learning.
Responsibilities
- Contribute to analytics initiatives using statistical and machine learning techniques to solve business problems in demand forecasting, pricing, and product optimization
- Support the development and improvement of analytical models to understand demand drivers and price elasticity
- Assist in building tools and analytical processes that improve trade spend effectiveness and promotional performance
- Support analytics initiatives that enhance operational planning and execution
- Create clear visualizations and collaborate with cross-functional teams to translate data insights into actionable recommendations
Requirements
- Bachelor’s degree or a college diploma in a quantitative or technical field such as Statistics, Mathematics, Data Science, Engineering
- 3+ years of experience in data science, advanced analytics, or applied machine learning roles
- Strong experience working with large, complex datasets and proficiency in SQL and Python
- Experience applying statistical modeling and machine learning techniques, such as regression-based models, tree-based models and optimization approaches
- Foundational understanding of demand forecasting, elasticity modeling, promotional analysis, or scenario modeling
- Familiarity with analytics development within Databricks and the Azure data ecosystem is considered an asset
- Strong proficiency in data visualization tools such as Power BI or Tableau
- Ability to communicate analytical concepts clearly to both technical and non-technical audiences
Benefits
- Comprehensive benefits package
- Access to retirement and saving programs
- Family and employee assistance program
- Paid vacation and floater days
- Professional development opportunities
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