Data Scientist Lead - Measurement and Experimentation

at  Sobeys

Requisition ID: 186938
Career Group: Corporate Office Careers
Job Category: Data Science - Marketing
Travel Requirements: 0 - 10%
Job Type: Full-Time
Country: Canada (CA)
Province: Ontario
City: Toronto
Location: Sobeys Innovation Hub
Embark on a rewarding career with Sobeys Inc., celebrated among Canada’s Top 100 employers, where your talents contribute to our commitment to excellence and community impact.
Our family of 128,000 employees and franchise affiliates share a collective passion for delivering exceptional shopping experiences and amazing food to all our customers. Our mission is to nurture the things that make life better – great experiences, families, communities, and our employees. We are a family nurturing families.
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 1,600 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.

WHAT YOU’LL GET TO DO IN THIS ROLE:

As the Data Science Lead - Measurement and Experimentation, you will provide technical leadership for a portfolio of measurement solutions covering a broad range of marketing, space productivity, and promotion planning use cases, including but not limited to A/B testing of stores for space optimization algorithm, and Bayesian measurement for marketing personalization program. You will partner with the Data Science, Business, Enterprise Data, Technology, Cybersecurity, Business Intelligence, and Engineering teams to translate measure and provide visibility into AI/ML solutions. You will work closely with the Data Science Director on measurement product direction and design decisions and oversee all technical aspects of the measurement solution for AI/ML applications, from design to deployment and sustainment. The successful candidate will be a self-directed, experienced applied data scientist who enjoys building advanced measurement ETLs from the ground up.

KEY RESPONSIBILITIES INCLUDE:

• Work directly with business stakeholders to translate business requirements and opportunities into statistical KPIs for measurement of AI/ML problems.
• Lead team of data scientists to build and manage statistical measurement ETLs for new AI/ML applications and continuously improve existing measurement algorithms in a scalable cloud development environment using Databricks; work in lockstep with the Engineering team to ensure proper workflow orchestration and automation across the full, end-to-end measurement ETLs.
• Own the development, implementation and sustainment of measurement and experimentation methodologies for AI/ML products across different levels of the business, including customer-level, product-level and store-level experiments (e.g., frequentist testing for stores, Bayesian test for customers in personalization program, and Markov chain multi-touch attribution modeling for retail media).
• Work closely with business stakeholders to translate measures of success and KPIs to statistical measures (e.g., incremental sales lift, contribution of certain media touchpoint to overall sales, and ROI) for all applications and use cases under your stewardship; partner with the Advanced Analytics Data Science teams on the development of AI/ML MLOPs pipelines and ensure measurement ETLs are developed in sync and reports to tracks various statistical metrics.
• Work closely with Business Intelligence (BI) teams in building, maintaining, and optimizing dashboards and find easy to understand messaging for advanced statistical metrics of various business stakeholders.
• Mentor and coach team by providing regular feedback and through code reviews and pair programming.
• Support production model governance processes and the development of robust quality controls for your algorithms.
• Work with peers across the Advanced Analytics team to drive MLOps, engineering, and coding best practices, global standards, and the build of common, reusable measurement components across the AA product portfolio.Stay up to date with best practices and latest advances in application of statistics, Bayesian statistics, and Markov chains in retail, and drive the adoption of the same across the team.