Market Analytics CO-OP Student-2

작업 내용

Term Length: 4 months Term Start: September 6th, 2022 Term End: December 16th, 2022 *COVID Vaccination Status / Return to Office*: COVID-19 is a serious condition and has had a devastating impact on Canadians and others across the globe. As a leading Health and Wellness provider for millions of Canadians, our goal is to help all Canadians "Live Life Well". In support of this goal, we have adopted a COVID-19 Vaccination Policy to protect the health and well-being of our employees as we continue our phased approach of office reopening. Store Support employees will be required either to be fully vaccinated or undergo regular COVID-19 Rapid Antigen Screening, paid for by the company, in order to access the workplace. As of March 2022 Loblaw has adopted the following Hybrid working model (a combination of working between the office and remotely).

Colleagues will continue working remotely up to 2 days a week, while spending the other 3 days in the office.

Position Overview: As a part of the Merchandising analytics team, the Loblaw co-op team will be leveraging data science concepts to identify opportunities, develop solutions and integrate them into our core business processes.

Our co-op program will include all aspects of merchandising including price elasticity and optimization, assortment optimization, customer segmentations, loyalty offer targeting, and portfolio management.

A successful co-op colleague will be:

• Passionate about data, algorithms, programming and statistics
• A motivated self-starter and a relentless problem solver
• Curious mindset to understand the business opportunities to apply data science concepts
• Eager to apply machine learning to solve real world problems
• Able to research technical concepts and solutions
• Excited to learn and teach new concepts and techniques
• Comfortable working on their own and within a team
• Excited about the opportunity to present to company executives
• Focused on improving processes for our stores and customers
• Able to manage multiple initiatives with firm deadlines
• Comfortable working in a professional environment interacting with all levels within the organization
• Qualifications:
• Enrolled in undergraduate degree similar to Computer Science, Engineering, Data Science and Statistics
• Programming experience in SQL and Python, R, or any other programming language
• Ability to convert data to insight, insight to recommendations and recommendations into an action plan
• Knowledge of AI and data science concepts (Machine learning, prescriptive analytics, neural networks, etc.)
• Familiarity with Git, Unix command line and bash scripting is an asset
• Experience with distributed computing (eg. Hadoop, Spark) is an asset
• Participation in Data Science Hackathons and/or a Github link to your data science related projects is an asset