Data Scientist I

at  CocaCola Canada Bottling Limited

QUALIFICATIONS

• Bachelor’s degree in a technical field or a quantitative field, Master’s degree is an asset.
• 3+ years of data science-based and analytics experience
• Strong proficiency in Python
• Databricks, Pyspark is considered an asset
• Experience in visualization tools such as Power Bl (preferred), Tableau or Qlikview
• Strong proficiency in statistical and machine learning techniques (Multivariate regression, Random Forests, XGBoost, Neural Networks)
• Strong proficiency in demand, elasticity, marketing mix, multi-arm bandit models, as well as linear and non linear optimization algorithms.
• Exceptional attention to detail and demonstrated ability to solve business problems through analytics.
• Ability to explain a data science project, problem, or insight in a story-telling manner to non-technical audience.
• Strong proficiency in advanced Excel, VBA/DAX an asset
• Prior experience in CPG or Retail industry an asset

ABOUT US: PROUDLY CANADIAN AND INDEPENDENTLY OWNED, WE ARE COKE CANADA!

Coca-Cola Canada Bottling Limited is Canada’s premier bottling company. We are an independently owned business encompassing over 5,800 associates, more than 50 sales and distribution centers, and 5 production facilities nationwide. For more information about Coke Canada Bottling, please visit cokecanada.com

• Key contributor for the development of Coke Canada commercial analytics tools and communication of implementation strategies
• Key contributor to the development of the trade spend optimization tools and processes for all channels in conjunction with other partner resources
• Key consult for partnership work on promotion offer testing (third-party) and ownership of post-audits for implementation opportunities and risk identification
• Development of analytics use cases for revenue and profit acceleration.
• Key consult within the process of planning the volume and revenue including scenario building, elasticity impacts, volume/rate/mix scenarios, and overall customer and category support.
• Support requests for analysis including ad-hoc, monthly, and YTD reporting with an emphasis on results vs predictions