Data Scientist - Toronto, Canada - Sobeys
Description
Requisition ID:179895
Career Group:
Corporate Office Careers
Job Category:
Advanced Analytics
Travel Requirements:0 - 10%
Job Type:
Full-Time
Country:
Canada (CA)
Province:
Ontario
City:
Toronto
Location:
Sobeys Innovation Hub
Postal Code:
M5V 1X6
Our family of 134,000 employees and franchise affiliates share a collective passion for delivering exceptional shopping experiences and amazing food to all our customers.
A proudly Canadian company, we started in a small town in Nova Scotia but we are now in communities of all sizes across this great country.
With over 1500 stores in all 10 provinces, you may know us as Sobeys, Safeway, IGA, Foodland, FreshCo, Thrifty Foods, Lawtons Drug Stores or another of our great banners but we are all one extended family.
All **career opportunities will be open a minimum of 5 business days from the date of posting.
Ready to Make an impact?:
The Advanced Analytics team at Sobeys operates on the frontlines of retail innovation.
We are a multi-disciplinary team of data scientists, engineers, developers, and analysts who design, develop, and deploy high-impact, scalable ML/AI solutions that are fundamentally transforming how Sobeys and its family of banners interact with customers and plan and operate their businesses.
We leverage the latest cloud tech and advanced analytical techniques to connect the dots between customer behaviour and business operations and unearth the true drivers of customer engagement, sales growth, and profitability.
Our work directly impacts the daily lives of millions of Canadian consumers and is a key pillar in our mission to deliver a best-in-class shopping experience for our customers.
Here's where you'll be focusing:
Responsibilities:
- Research, build, train, serve, and monitor machine learning (ML) models
- Work closely with Machine Learning Engineers (MLE), Data Engineers (DE), and other Data Scientists in the same team to create and manage endtoend ML pipeline in Azure cloud development environment
- Write production ready code that will be reviewed by other team members and review their code
- Work with MLEs to scale, automate and optimize ML pipelines
- Work with DEs to ETL in a big data environment consistent of billions of rows of retail data covering many banners, regions, and millions of customers
- Work closely with various stakeholders throughout our business to understand business needs and develop solutions through machine learning or other advanced analytics/predictive modeling techniques
- Work with BI team to create dashboards that monitor performance of your ML systems
What you have to offer:
- Master's degree or higher in Computer Science, Engineering, Statistics, Mathematics, or a related technical field.
- 3+ years of experience with mathematical optimization and the productionization of optimization solutions.
- 3+ years of handson experience in developing endtoend machinelearning algorithms in cloud or distributed environments using Python, Java, or Scala.
- 3+ years of experience with distributed ML platforms, such as Spark ML, ML Flow, and TensorFlow.
- 3+ years of experience manipulating large datasets using Spark or SQL.
- 3+ years of experience in cloud CI/CD environments, such as Azure DevOps or Bitbucket Pipelines.
- Proven ability to engage with stakeholders to gather requirements and communicate updates effectively.
- Creative mindset, excellent communication skills, and the ability to create and manage ML pipelines with mínimal guidance.
- 2+ years of experience building executivelevel dashboards in Tableau or similar tools like Google Data Studio.
- Familiarity with Cloud Environments, specifically Databricks and Azure, is a significant asset.
- Experience in Retail or similar settings is an additional asset.
Sobeys is committed to accommodating applicants with disabilities throughout the hiring process and will work with applicants requesting accommodation at any stage of this process.
**We appreciate the interest from the Staffing industry however respectfully request no calls or unsolicited resumes from Agencies.
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