Manager, Advanced Analytics & Modelling

Canadian Tire Corporation • Toronto, ON

64d

About The Position

We are seeking a an experienced data science leader to lead a team of talented data scientists and statisticians within CTC’s Advanced Analytics, Modelling, and Experimentation function. The primary focus of this team will be to develop machine learning and other mathematical models and solutions in support of our merchandising, pricing, promotional, customer engagement, loyalty, and marketing programs. Your team will also deliver analytical measurement frameworks, construct advanced statistical models, build causal inference models, and perform customer and program analytics. This role is critical to the execution of our bold true North strategy. This role reports to the AVP, Advanced Analytics, Modelling & Experimentation. In order to achieve the desired business outcomes, the successful candidate is expected to work closely with a wide variety of colleagues and partners within the broader Customer Analytics and Predictive Modelling team, as well as across Pricing and Promotion, Customer Strategy and Enablement, Enterprise Retail Planning, Triangle Loyalty, Marketing and Digital, Technology and all of our retail business teams. What You’ll Do Develop a deep understanding of our Retail businesses and Loyalty Program. Establish the credibility required to influence business decisions which rely on data science and modelling. Lead the development of advanced quantitative and statistical models on retail, customer and loyalty data to build solutions and generate timely insights with the purpose of executing on business strategic objectives and improving existing business processes. Establish robust modelling practices as well as experimental and measurement frameworks utilizing latest technologies and advancements in statistics and machine learning. Build and deploy Machine Learning/Deep Learning models which can adapt to constantly evolving data and problem sets. Seek out opportunities to infuse statistical learning to support the decision-making process for clients, strategic initiatives and key business stakeholders. Provide creative solutions, recommendations and timely advice that synthesize business needs and analytical/modelling concepts. Build a knowledgeable, engaged, and aligned data science and modelling team. Foster the development of talent and establish systems to ensure career progression within your team, Advanced Analytics, Modelling & Experimentation, and the larger analytics community within CTC. Act as an active contributor to the analytics strategy within the Advanced Analytics team. Who You Are We are looking for high performing individuals who are: Strategically minded data science and modelling professionals, who can navigate within an environment of change and ambiguity. Motivated problem solver who works well within a fast-paced environment. Capable of overseeing multiple complex modelling efforts at the same time, while meeting the demands of clients and senior business leaders. Creative thinkers who take initiative and are capable of building, launching, and managing projects/programs that drive results for our business partners. Inclusive leaders who build and develop a team that effectively anticipates and responds to disruption, while consistently delivering strong performance. If you’re curious, ready to take on new challenges and open to doing things differently to help us evolve rapidly, then Canadian Tire is the place for you! What You Bring Post-secondary (Graduate-level) education, preferably PhD, in Statistics/Math/Economics/Data Science/Computer Science or a related quantitative discipline 4+ years experience leading analytical functions within large organizations within the areas of advanced analytics, machine learning and statistical/mathematical modelling. Deep understanding of a variety of mathematical statistics, graduate-level probability & statistics and stochastic processes, causal modelling and advanced hypothesis testing. Strong quantitative and statistical skills (regression/prediction, ML/DL techniques, statistical learning, model inference, model validation, etc.) 4+ years working experience with Python as an analytical tools and programming language. 4+ years of experience querying and analyzing large datasets with tools such as SQL, Spark, etc. Experience working in BigData environments (Hadoop, Databricks, etc), as well as cloud environments (Azure, AWS, etc). 4+ years interpreting, synthesizing, and presenting complex models and analysis to non-technical senior business leaders. Excellent communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills. Demonstrated confidence, leadership presence and clear presentation style.

Requirements

• Post-secondary (Graduate-level) education, preferably PhD, in Statistics/Math/Economics/Data Science/Computer Science or a related quantitative discipline
• 4+ years experience leading analytical functions within large organizations within the areas of advanced analytics, machine learning and statistical/mathematical modelling.
• Deep understanding of a variety of mathematical statistics, graduate-level probability & statistics and stochastic processes, causal modelling and advanced hypothesis testing.
• Strong quantitative and statistical skills (regression/prediction, ML/DL techniques, statistical learning, model inference, model validation, etc.)
• 4+ years working experience with Python as an analytical tools and programming language.
• 4+ years of experience querying and analyzing large datasets with tools such as SQL, Spark, etc.
• Experience working in BigData environments (Hadoop, Databricks, etc), as well as cloud environments (Azure, AWS, etc).
• 4+ years interpreting, synthesizing, and presenting complex models and analysis to non-technical senior business leaders.
• Excellent communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills.
• Demonstrated confidence, leadership presence and clear presentation style.

Responsibilities

• Develop a deep understanding of our Retail businesses and Loyalty Program.
• Establish the credibility required to influence business decisions which rely on data science and modelling.
• Lead the development of advanced quantitative and statistical models on retail, customer and loyalty data to build solutions and generate timely insights with the purpose of executing on business strategic objectives and improving existing business processes.
• Establish robust modelling practices as well as experimental and measurement frameworks utilizing latest technologies and advancements in statistics and machine learning.
• Build and deploy Machine Learning/Deep Learning models which can adapt to constantly evolving data and problem sets.
• Seek out opportunities to infuse statistical learning to support the decision-making process for clients, strategic initiatives and key business stakeholders.
• Provide creative solutions, recommendations and timely advice that synthesize business needs and analytical/modelling concepts.
• Build a knowledgeable, engaged, and aligned data science and modelling team.
• Foster the development of talent and establish systems to ensure career progression within your team, Advanced Analytics, Modelling & Experimentation, and the larger analytics community within CTC.
• Act as an active contributor to the analytics strategy within the Advanced Analytics team.

Benefits

• Comprehensive benefits and retirement programs
• Performance incentives
• Continuing Education Programs
• Other perks to support your well-being
• Career growth opportunities and product discounts
• Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees.
• As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: Ph.D. or professional degree