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Data Scientist Lead – Measurement and Experimentation
Location:
Sobeys COLAB Office (Toronto Downtown)
Team:
Advanced Analytics
Overview The Advanced Analytics team at Sobeys operates on the front lines of retail innovation. We are a multi-disciplinary team of data scientists, engineers, software developers, architects, and analysts who design, develop, and deploy high-impact, scalable measurement for AI/ML products and services that are fundamentally transforming how Sobeys and its family of banners interact with customers and operate their businesses. We leverage the latest cloud technology 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 become the #1 retail brand in Canada.
Here’s Where You’ll Be Focusing 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…
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