Senior Manager Of Data Science & Data Products

The Senior Manager, Data Science & Data Products is the leader responsible for defining the strategy, requirements and delivering data products that power data science for a Omni-channel business in pursuit of growth and efficiency. This data /analytics leader collaborates with senior leaders across operations, technology, finance, merchandising and strategic business (ex: Online Grocery, Marketplace) and builds data products to solve critical business needs. As the data science thought leader, this role will evangelize adoption of Machine Learning /AI and introduce new leading edge data technologies across the enterprise. The successful candidate will have an established background in solving complex problems, a strong technical ability, excellent product/project management skills, great communication skills, and the motivation to achieve results in a fast-paced environment. The role offers an unparalleled opportunity that combines, world class technical infrastructure, ability to leverage global resources/knowledge, large amounts of data, complex business problems and ample leeway to lead the data science practice in new directions. This is a dream job for a curious, analytical mind that longs to push the boundaries of what’s possible.

What you'll do...

• Partner with Data Science leaders across the organization to share best practices, methods and technologies and collaborate to elevate the discipline within the company.
• Lead a cross-functional po team of experimentation/research/UX specialists and other internal partners to envision, build, test and deliver experiences that impact tens of millions of consumers.
• As customer behaviour analytics thought leader, partner with and guide the development of CRM across technology and marketing domains to ensure end product delivers on business needs while serving our customers.
• As subject matter expert in advanced analytical methods lead critical unit, sales and channel forecasting function, output of which guides op-ex and cap-exe budget planning both short (month) and long term (3YP).
• Lead the integration of data science capabilities with functional business needs to solve tangible problems with measurable impact.
• Lead the overall strategy and execution of the Data Science, Data Products and Research and Optimization function within Canada eCommerce, specifically managing resource prioritization to deliver the highest return.
• Build and execute a long term roadmap of elevating data science capabilities within company by researching, piloting and introducing leading edge data technologies and products.
• Build relationships and collaborate with senior leader stakeholders in Operations, Merchandising, Finance, Technology and Marketing to identify opportunities where Machine Learning, AI or other data products can resolve issues, improve efficiency or reduce cost.

Qualifications:

• Expert at data and model management
• Able at preparing presentation content for diverse audience groups
• Extensive experience in building Logic/ML-based Predictive Models and Optimization Models
• Strong ability to work cross-functionally, effectively gathering or giving feedback
• Strong in scalable data manipulation technologies such as Spark, Pandas, Polars
• Excellent analytical and data interpretation skills with natural curiosity and strong attention to detail • Strong problem-solver, with ability to handle ambiguous and open-ended problems
• Strong Oral and Written communicator, able to convey complex ideas in simple terms
• 8+ years of experience working in analytics or data-science function. Background in software engineering is a plus
• Bachelors/Master’s in engineering, Computer Science, Applied Mathematics, Operations Research or related field, with focus on Business Management
• 1-3 years of direct people leadership experience

Tools

• Technical Experience working with customer data platforms, event-level data, ML & feature engineering pipelines
• Knowledge Web Deployment frameworks such Streamlit/Rshiny
• Comfortable writing/reviewing code written in SQL, Python, R, and leveraging machine learning frameworks & toolkits such as PyTorch, TensorFlow, Spark, or scikit-learn