Description:
We are recruiting for a Data Scientist to join our Data Science and Advanced Analytics team. This Advanced Analytics role is part of the broader Technology function and plays a key role in supporting high impact, data driven initiatives across the organization. The team partners with stakeholders in commercial strategy, sales execution, and operations to address complex business challenges through advanced analytics and machine learning.
As a Data Scientist, you will contribute to cross functional projects involving demand modeling, promotion and trade spend optimization, pricing and elasticity analysis, network and inventory optimization, and scenario modeling. You will work closely with business partners to translate exploratory analytical work into scalable, production ready solutions that enhance planning, strengthen decision making, and improve execution across the organization
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, ensuring insights are practical, reliable, and business-relevant.
- Assist in building tools and analytical processes that improve trade spend effectiveness and promotional performance, enabling smarter commercial and sales decisions.
- Support analytics initiatives that enhance operational planning and execution, applying data-driven insights as the function expands into operations-focused areas.
- Create clear visualizations and collaborate with cross-functional teams to translate data insights into actionable recommendations for commercial, sales, and operations stakeholders.
Qualifications
- Bachelor’s degree or a college diploma in a quantitative or technical field (e.g., Statistics, Mathematics, Data Science, Engineering); a Master’s degree is considered an asset.
- 3+ years of experience in data science, advanced analytics, or applied machine learning roles, with exposure to business-focused analytics.
- 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 (preferred) or Tableau.
- Ability to communicate analytical concepts clearly to both technical and non-technical audiences.
- Proactive mindset with the ability to work through ambiguity, take initiative, and suggest new analytical approaches or opportunities to improve business outcomes.