Senior Data Scientist
About The Position
The Senior Data Scientist, Advanced Analytics role sits within the Advanced Analytics function under the Technology team and reports to the Senior Manager, Data Science. The Advanced Analytics team partners across the enterprise to solve complex, high-impact business challenges using data, analytics, and machine learning. This work spans areas such as commercial strategy, sales execution, and supply chain, including demand modeling, promotion and trade spend optimization, pricing and elasticity analysis, network and inventory optimization, and scenario modeling. In this role, you will contribute to cross-functional initiatives, working closely with business stakeholders to apply advanced analytics solutions. You will support the development of scalable, production-ready models and help embed data-driven decision-making across planning, operations, and execution.
Requirements
- Bachelor’s degree in a quantitative or technical field (e.g., Statistics, Mathematics, Data Science, Engineering); Master’s degree is an asset.
- 5+ years of experience in data science, advanced analytics, or applied machine learning roles, with demonstrated business impact.
- 1–3 years of experience in Machine Learning Operations (MLOps).
- Strong experience working with large, complex datasets, with advanced proficiency in SQL and Python.
- Deep expertise in statistical modeling and machine learning techniques, such as regression models and tree-based models (e.g., Random Forest, XGBoost), as well as optimization approaches.
- Experience designing and delivering end-to-end analytics solutions, from exploration through deployment.
- Experience deploying machine learning models into production, including monitoring for data and model drift.
- Strong understanding of demand forecasting, elasticity modeling, promotional analysis, and scenario modeling.
- Proficiency in data visualization and storytelling using tools such as Power BI (preferred) or Tableau.
- Ability to communicate complex analytical concepts clearly to both technical and non-technical audiences.
Nice To Haves
- Familiarity with Databricks and the Azure data ecosystem is an asset.
Responsibilities
- Lead initiatives that apply analytics and advanced techniques to deliver actionable solutions for the business.
- Enhance and maintain analytical models focused on understanding demand drivers and price elasticity, ensuring they deliver actionable insights for the business.
- Manage the end-to-end deployment pipeline for machine learning models, establishing robust monitoring for data drift, model drift, and performance degradation.
- Transition prototype models into reliable, reproducible, and scalable production pipelines.
- Apply statistical and machine learning techniques to solve complex problems in demand forecasting, product optimization, and business decision-making.
- Create engaging data visualizations to communicate insights clearly to both technical and non-technical stakeholders, enhancing decision-making and strategy development.
- Collaborate across teams including product managers, engineers, and business leaders, to turn data insights into practical solutions and recommendations that drive business impact.
Benefits
- competitive compensation package
- access to retirement and saving programs
- family and employee assistance program
- paid vacation and floater days
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What This Job Offers
Job Type
Full-time
Career Level
Senior
