Data Science Lead - Marketing

at  Sobeys

Requisition ID: 186799
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.

QUALIFICATIONS:

• Master’s or PhD degree in Computer Science, Engineering, Statistics, Mathematics, or related technical field.
• 5+ years of industry experience working as a data scientist or similar roles, with at least 2+ years of direct people management or team leadership experience.
• Significant experience in end-to-end development and productionization of large-scale ML pipelines using Python in a cloud environment (e.g., Databricks, Snowflake, Azure Synapse, AWS SageMaker), including model deployment, monitoring, and scalability.
• Familiarity with MLflow, Airflow, and similar MLOps platforms is a plus.
• Experience developing and operationalizing marketing mix models in a retail or other B2C setting, with a focus on optimizing media/marketing planning and maximizing ROAS.
• Experience building and deploying customer lifetime value (CLTV) models, as well as models for churn prediction and customer retention.
• Experience in building and/or deploying large-scale personalization algorithms (e.g., recommender systems, targeted messaging) to drive customer engagement and retention is highly desirable.
• Strong experience with data manipulation using PySpark and SQL.
• Extensive hands-on experience with machine learning and statistical modeling techniques using Python – experience using packages such as StatsModel, SparkML, DoWhy, EconML is a big plus.
• Strong leadership and mentoring skills, with a proven ability to guide a team of data scientists to achieve ambitious goals and foster a collaborative environment.
• Proven experience managing multiple stakeholders, concurrent workstreams, priorities and deadlines in a high pressure, fast-paced environment.
• Excellent communication skills, with the ability to explain and present complex technical concepts to both technical and non-technical audiences.
  While all responses are appreciated only those being considered for interviews will be acknowledged.

WHAT YOU’LL GET TO DO IN THIS ROLE:

As the Data Science Lead - Marketing, you will provide technical leadership for a portfolio of intelligent solutions covering a broad range of marketing use cases, including customer lifecycle management, marketing optimization, and personalized pricing. You will partner with the Business, Enterprise Data, Technology, Cybersecurity, and Engineering teams to translate business requirements and opportunities into AI/ML problems, and trained models into secure, reliable, enterprise-scale applications. You will work closely with the Marketing Data Science Director on product direction and design decisions and oversee all technical aspects of the AI/ML development lifecycle, from design to deployment and sustainment. The successful candidate will be a self-directed, experienced applied data scientist who enjoys building intelligent systems from the ground up.

RESPONSIBILITIES:

• Work directly with business stakeholders to translate business requirements and opportunities into AI/ML problems.
• Lead team of data scientists to build and manage model engineering pipelines for new use cases and continuously improve existing 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 MLOps pipeline.
• Own the development, implementation, and sustainment of customer lifecycle (e.g., churn prevention, e-commerce activation, etc.), lifetime value, and marketing mix models to drive customer engagement and retention, and optimize media/marketing planning and investment.
• Develop and implement algorithm(s) to enable personalized pricing across participating Scene+ banners.
• Partner with the Business, Engineering, Enterprise Data, Cybersecurity, and Technology teams, and third parties to operationalize algorithms in the business.
• Work closely with business stakeholders to define measures of success and KPIs for all applications and use cases under your stewardship; partner with the Advanced Analytics Measurement & Experimentation COE on measurement strategy and the development of measurement ETL and reporting to track incremental business benefits and guide development efforts.
• 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 components across the AA product portfolio.
• Stay up to date with best practices and latest advances in marketing science, personalization, and machine learning, and drive the adoption of the same across the team.